Publications

A word’s predictability or surprisal in linguistic context, as determined by cloze probabilities or languagemodels (e.g. Frank, 2013a) is related to processing effort, in that less expected words take more effort to process (e.g. Hale, 2001). This shows how, in purely linguistic contexts, rational approaches have been proven valid to predict and formalise results from language processing studies. However, the surprisal (or predictability) of a word may also be influenced by extra-linguistic factors, such as visual context information, as given in situated language processing. While, in the case of linguistic contexts, it is known that the incrementally processed information affects the mental model (e.g. Zwaan and Radvansky, 1998) at each word in a probabilistic way, no such observations have been made so far in the case of visual context information. Although it has been shown that in the visual world paradigm (VWP), anticipatory eye movements suggest that listeners exploit the scene to predict what will be mentioned next (Altmann and Kamide, 1999), it is so far unclear how visual information actually affects expectations for and processing effort of target words. If visual context effects on word processing effort can be observed, we hypothesise that rational concepts can be extended in order to formalise these effects, hereby making them statistically accessible for language models. In a line of experiments, I hence observe how visual information – which is inherently different from linguistic context, for instance in its non-incremental-at once-accessibility– affects target words. Our findings are a clear and robust demonstration that the non-linguistic context can immediately influence both lexical expectations, and surprisal-based processing effort as assessed by two different on-line measures of effort (a pupillary and an EEG one). Finally, I use surprisal to formalise the measured results and propose an extended formula to take visual information into account.

• http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-284518
• https://doi.org/http://dx.doi.org/10.22028/D291-28451

@phdthesis{Ankener_diss_2019,
title = {The influence of visual information on word predictability and processing effort},
author = {Christine Ankener},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-284518},
doi = {https://doi.org/http://dx.doi.org/10.22028/D291-28451},
year = {2019},
date = {2019},
school = {Saarland University},
address = {Saarbruecken, Germany},
abstract = {A word’s predictability or surprisal in linguistic context, as determined by cloze probabilities or languagemodels (e.g. Frank, 2013a) is related to processing effort, in that less expected words take more effort to process (e.g. Hale, 2001). This shows how, in purely linguistic contexts, rational approaches have been proven valid to predict and formalise results from language processing studies. However, the surprisal (or predictability) of a word may also be influenced by extra-linguistic factors, such as visual context information, as given in situated language processing. While, in the case of linguistic contexts, it is known that the incrementally processed information affects the mental model (e.g. Zwaan and Radvansky, 1998) at each word in a probabilistic way, no such observations have been made so far in the case of visual context information. Although it has been shown that in the visual world paradigm (VWP), anticipatory eye movements suggest that listeners exploit the scene to predict what will be mentioned next (Altmann and Kamide, 1999), it is so far unclear how visual information actually affects expectations for and processing effort of target words. If visual context effects on word processing effort can be observed, we hypothesise that rational concepts can be extended in order to formalise these effects, hereby making them statistically accessible for language models. In a line of experiments, I hence observe how visual information – which is inherently different from linguistic context, for instance in its non-incremental-at once-accessibility– affects target words. Our findings are a clear and robust demonstration that the non-linguistic context can immediately influence both lexical expectations, and surprisal-based processing effort as assessed by two different on-line measures of effort (a pupillary and an EEG one). Finally, I use surprisal to formalise the measured results and propose an extended formula to take visual information into account.},
pubstate = {published},
type = {phdthesis}
}

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Questions under Discussion (QUDs) have been suggested to influence the integration of individual utterances into a discourse-level representation. Previous work has shown that processing ungrammatical ellipses is facilitated when the elided material addresses an implicit QUD raised through a nonactuality implicature (NAIs). It is not clear, however, if QUDs influence discourse coherence during comprehension of fully acceptable discourse. We present two ERP studies examining the effects of QUDs introduced by NAIs using two-sentence discourses. Experiment 1 showed that processing definite NPs with inaccessible antecedents is facilitated when their content is relevant to the QUD. Using acceptable discourses, Experiment 2 showed that definite NPs failing to address a QUD elicit increased processing cost. Overall, our results indicate that QUDs raise the expectation that the following discourse will address them, providing unambiguous evidence that their influence is not limited to the processing of ungrammatical input.

• https://doi.org/10.1080/0163853X.2019.1575140
• https://doi.org/10.1080/0163853X.2019.1575140

@article{Delogu2019b,
title = {Discourse Expectations Are Sensitive to the Question Under Discussion: Evidence From ERPs},
author = {Francesca Delogu and Torsten Jachmann and Maria Staudte and Francesco Vespignani and Nicola Molinaro},
url = {https://doi.org/10.1080/0163853X.2019.1575140},
doi = {https://doi.org/10.1080/0163853X.2019.1575140},
year = {2019},
date = {2019},
journal = {Discourse Processes},
pages = {1-19},
abstract = {Questions under Discussion (QUDs) have been suggested to influence the integration of individual utterances into a discourse-level representation. Previous work has shown that processing ungrammatical ellipses is facilitated when the elided material addresses an implicit QUD raised through a nonactuality implicature (NAIs). It is not clear, however, if QUDs influence discourse coherence during comprehension of fully acceptable discourse. We present two ERP studies examining the effects of QUDs introduced by NAIs using two-sentence discourses. Experiment 1 showed that processing definite NPs with inaccessible antecedents is facilitated when their content is relevant to the QUD. Using acceptable discourses, Experiment 2 showed that definite NPs failing to address a QUD elicit increased processing cost. Overall, our results indicate that QUDs raise the expectation that the following discourse will address them, providing unambiguous evidence that their influence is not limited to the processing of ungrammatical input.},
pubstate = {published},
type = {article}
}

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A large body of contemporary psycholinguistic research utilizes the information-theoretic notions related to the transmission of information in an attempt to better understand and formalize the regularities of language production and comprehension. The overarching hypothesis is that prediction is a core mechanism underlying language comprehension. Anticipating what is likely to be mentioned next based on the previous context is what is assumed to allow for smooth and effortless communication. The anticipation of linguistic units that fit the current context reduces the uncertainty about the upcoming material, which consequently facilitates the processing of that material, in a typically noisy channel. Situated language processing allows for the integration of not only linguistic but also non-linguistic visual information that contribute to establishing the context, and facilitate the creation of anticipations regarding the upcoming linguistic material. Moreover, noticing that our interlocutor is directing her attention to a certain object, inspires a shift in our visual attention towards the same entity. Since what is relevant for our interlocutor is highly likely to be relevant for us, too, whether simply conversationally, or more importantly, even existentially (Emery, 2000). Hence, following the speaker’s referential gaze cue towards an object relevant for the current conversation has been shown to benefit listeners’ language processing, measured by shorter reaction times on subsequent tasks (e.g., Staudte & Crocker, 2011; Staudte, Crocker, Heloir, & Kipp, 2014; Knoeferle & Kreysa, 2012; Macdonald & Tatler, 2013, 2014). The present thesis aimed to provide an insight into the mechanisms behind this facilitation. We examined the dynamics of combining visual and linguistic information in creating anticipation for a specific object to be mentioned, and the effect this has on language processing. To this end we used a pupillary measure of cognitive load that is robust enough to allow for free eye movements (the Index of Cognitive Activity; Marshall, 2000). This enabled us to measure not only the visual attention during language comprehension, but also the immediately induced cognitive load at various relevant points during the auditory presentation of the linguistic stimulus. Eight experiments were conducted towards addressing our research questions. The initial three experiments established the ICA measurement in the context of our linguistic manipulation. This series of experiments included reading, cognitive load during listening, and the examination of visual attention together with cognitive load in the visual world paradigm (VWP). Subsequently, we conducted five eye tracking experiments in the VWP where the linguistic context was further enriched by a referential gaze cue. All five experiments simultaneously assessed both visual attention and the immediate cognitive load induced at different stages of sentence processing. We manipulated the existence of the referential gaze cue (Exp. 4), the probability of mention of the cued object (Exp. 4, 5), the congruency of the gaze cue and the subsequent referring expression (Exp. 6), as well as the number of cued objects with equal probability of mention (Exp. 7, 8). Finally, we examined whether the gaze cue can take the role of fully disambiguating the target referent (Exp. 8). We quantified the importance of the visual context in language processing, and showed that if a certain object from the visual context has a higher likelihood of mention given the linguistic context, its processing is facilitated, in comparison to the processing of the same sentence without the visual context. Furthermore, our results support the previous findings that the referential gaze cue leads to a shift in visual attention towards the cued object, thereby facilitating language processing. We expanded these findings by showing that it is the processing of the linguistic reference, that is the referent noun, that is facilitated by gaze-following. Importantly, perceiving and following the gaze cue did not prove costly in terms of cognitive effort, unless the cued object did not fit the verb selectional preferences. This is true regardless of the number of objects cued, or the lower likelihood of mention of the cued object. We conclude that listeners strategically use visual information to reduce the referential uncertainty for upcoming nouns but that the visual cues, such as the referential gaze cue, do not underly the same kinds of expectations (and resulting cognitive costs) as linguistic references. We did not find evidence that the gaze cue is processed in a manner comparable to noun processing, rather, it is likely perceived as a relevant piece of information introduced in addition to the linguistic material, in order to aid language processing, but, importantly, not there to substitute it.

• http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-285651
• https://doi.org/http://dx.doi.org/10.22028/D291-28565

@phdthesis{Sekicki_diss_0919,
title = {Exploiting referential gaze for uncertainty reduction in situated language processing: an information-theoretic approach},
author = {Mirjana Sekicki},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-285651},
doi = {https://doi.org/http://dx.doi.org/10.22028/D291-28565},
year = {2019},
date = {2019},
school = {Saarland University},
address = {Saarbr{\"u}cken},
abstract = {A large body of contemporary psycholinguistic research utilizes the information-theoretic notions related to the transmission of information in an attempt to better understand and formalize the regularities of language production and comprehension. The overarching hypothesis is that prediction is a core mechanism underlying language comprehension. Anticipating what is likely to be mentioned next based on the previous context is what is assumed to allow for smooth and effortless communication. The anticipation of linguistic units that fit the current context reduces the uncertainty about the upcoming material, which consequently facilitates the processing of that material, in a typically noisy channel. Situated language processing allows for the integration of not only linguistic but also non-linguistic visual information that contribute to establishing the context, and facilitate the creation of anticipations regarding the upcoming linguistic material. Moreover, noticing that our interlocutor is directing her attention to a certain object, inspires a shift in our visual attention towards the same entity. Since what is relevant for our interlocutor is highly likely to be relevant for us, too, whether simply conversationally, or more importantly, even existentially (Emery, 2000). Hence, following the speaker’s referential gaze cue towards an object relevant for the current conversation has been shown to benefit listeners’ language processing, measured by shorter reaction times on subsequent tasks (e.g., Staudte & Crocker, 2011; Staudte, Crocker, Heloir, & Kipp, 2014; Knoeferle & Kreysa, 2012; Macdonald & Tatler, 2013, 2014). The present thesis aimed to provide an insight into the mechanisms behind this facilitation. We examined the dynamics of combining visual and linguistic information in creating anticipation for a specific object to be mentioned, and the effect this has on language processing. To this end we used a pupillary measure of cognitive load that is robust enough to allow for free eye movements (the Index of Cognitive Activity; Marshall, 2000). This enabled us to measure not only the visual attention during language comprehension, but also the immediately induced cognitive load at various relevant points during the auditory presentation of the linguistic stimulus. Eight experiments were conducted towards addressing our research questions. The initial three experiments established the ICA measurement in the context of our linguistic manipulation. This series of experiments included reading, cognitive load during listening, and the examination of visual attention together with cognitive load in the visual world paradigm (VWP). Subsequently, we conducted five eye tracking experiments in the VWP where the linguistic context was further enriched by a referential gaze cue. All five experiments simultaneously assessed both visual attention and the immediate cognitive load induced at different stages of sentence processing. We manipulated the existence of the referential gaze cue (Exp. 4), the probability of mention of the cued object (Exp. 4, 5), the congruency of the gaze cue and the subsequent referring expression (Exp. 6), as well as the number of cued objects with equal probability of mention (Exp. 7, 8). Finally, we examined whether the gaze cue can take the role of fully disambiguating the target referent (Exp. 8). We quantified the importance of the visual context in language processing, and showed that if a certain object from the visual context has a higher likelihood of mention given the linguistic context, its processing is facilitated, in comparison to the processing of the same sentence without the visual context. Furthermore, our results support the previous findings that the referential gaze cue leads to a shift in visual attention towards the cued object, thereby facilitating language processing. We expanded these findings by showing that it is the processing of the linguistic reference, that is the referent noun, that is facilitated by gaze-following. Importantly, perceiving and following the gaze cue did not prove costly in terms of cognitive effort, unless the cued object did not fit the verb selectional preferences. This is true regardless of the number of objects cued, or the lower likelihood of mention of the cued object. We conclude that listeners strategically use visual information to reduce the referential uncertainty for upcoming nouns but that the visual cues, such as the referential gaze cue, do not underly the same kinds of expectations (and resulting cognitive costs) as linguistic references. We did not find evidence that the gaze cue is processed in a manner comparable to noun processing, rather, it is likely perceived as a relevant piece of information introduced in addition to the linguistic material, in order to aid language processing, but, importantly, not there to substitute it.},
pubstate = {published},
type = {phdthesis}
}

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Prior studies on language processing in aging have shown that older adults experience integration difficulties for contextually unpredictable target words (as indicated by low cloze probabilities in prior ratings), and that such comprehension difficulties are more likely to occur under more demanding processing conditions (e.g., dual-task situations). However, these effects have primarily been demonstrated for conditions when cloze probability of the linguistic stimuli was very low. The question we asked here was do dual-task demands also impair comprehension when target words provide a good, but not perfect, match with prior context? We used a dual-task design, consisting of a sentence comprehension and secondary motor tracking task. Critical target words were those which were not perfectly predictable based on context (words with a cloze probability of 0.7), as opposed to words that were near perfectly predictable based on context (cloze probabilities of 0.99). As a measure to index online processing difficulty for less expected target words, we took into account participants’ pupil size. Separate mixed effects models were fit for language comprehension, motor tracking, and pupil size, showing the following: (1) dual-task demands led to age-related comprehension difficulties when target words were less expected (as opposed to very highly expected), (2) integration difficulty in older adults was related to cognitive overload as less expected sentence continuations progressed over time, resulting in behavioral trade-offs between language comprehension and motor tracking, and (3) lower levels of working memory were predictive of whether or not older adults experienced cognitive overload when processing less expected words. In sum, more demanding processing conditions lead to comprehension impairments when words are highly unpredictable based on context, as many prior studies showed. Comprehension impairments among older individuals also occur for conditions when words provide a good, but not perfect, match with prior context. Higher working memory capacity can alleviate such impairments in older adults, thereby suggesting that only high-WM older adults have sufficient cognitive resources to pre-activate words that complete a sentence context plausibly, but not perfectly.

• https://www.frontiersin.org/articles/10.3389/fpsyg.2019.00709/full
• https://doi.org/10.3389/fpsyg.2019.00709

@article{Häuser2019,
title = {Effects of aging and dual-task demands on the comprehension of less expected sentence continuations: Evidence from pupillometry},
author = {Katja H{\"a}user and Vera Demberg and Jutta Kray},
url = {https://www.frontiersin.org/articles/10.3389/fpsyg.2019.00709/full},
doi = {https://doi.org/10.3389/fpsyg.2019.00709},
year = {2019},
date = {2019},
journal = {Frontiers in Psychology},
volume = {10},
abstract = {Prior studies on language processing in aging have shown that older adults experience integration difficulties for contextually unpredictable target words (as indicated by low cloze probabilities in prior ratings), and that such comprehension difficulties are more likely to occur under more demanding processing conditions (e.g., dual-task situations). However, these effects have primarily been demonstrated for conditions when cloze probability of the linguistic stimuli was very low. The question we asked here was do dual-task demands also impair comprehension when target words provide a good, but not perfect, match with prior context? We used a dual-task design, consisting of a sentence comprehension and secondary motor tracking task. Critical target words were those which were not perfectly predictable based on context (words with a cloze probability of 0.7), as opposed to words that were near perfectly predictable based on context (cloze probabilities of 0.99). As a measure to index online processing difficulty for less expected target words, we took into account participants’ pupil size. Separate mixed effects models were fit for language comprehension, motor tracking, and pupil size, showing the following: (1) dual-task demands led to age-related comprehension difficulties when target words were less expected (as opposed to very highly expected), (2) integration difficulty in older adults was related to cognitive overload as less expected sentence continuations progressed over time, resulting in behavioral trade-offs between language comprehension and motor tracking, and (3) lower levels of working memory were predictive of whether or not older adults experienced cognitive overload when processing less expected words. In sum, more demanding processing conditions lead to comprehension impairments when words are highly unpredictable based on context, as many prior studies showed. Comprehension impairments among older individuals also occur for conditions when words provide a good, but not perfect, match with prior context. Higher working memory capacity can alleviate such impairments in older adults, thereby suggesting that only high-WM older adults have sufficient cognitive resources to pre-activate words that complete a sentence context plausibly, but not perfectly.},
pubstate = {published},
type = {article}
}

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Impaired Semantic Verbal Fluency (SVF) in dementia due to Alzheimer’s Disease (AD) and its precursor Mild Cognitive Impairment (MCI) is well known. Yet, it remains open whether this impairment mirrors the breakdown of semantic memory retrieval processes or executive control processes. Therefore, qualitative analysis of the SVF has been proposed but is limited in terms of methodology and feasibility in clinical practice. Consequently, research draws no conclusive picture which of these afore-mentioned processes drives the SVF impairment in AD and MCI. This study uses a qualitative computational approach – combining temporal and semantic information – to investigate exploitation and exploration patterns as indicators for semantic memory retrieval and executive control processes. Audio SVF recordings of 20 controls (C, 66-81 years), 55 MCI (57-94 years) and 20 AD subjects (66-82 years) were assessed while groups were matched according to age and education. All groups produced, on average, the same amount of semantically related items in rapid succession within word clusters. Conversely, towards AD, there was a clear decline in semantic as well as temporal exploration patterns between clusters. Results strongly point towards preserved exploitation – semantic memory retrieval processes – and hampered exploration – executive control processes – in AD and potentially in MCI.

• https://www.sciencedirect.com/science/article/abs/pii/S0028393218305116?via%3Dihub
• https://doi.org/10.1016/j.neuropsychologia.2019.05.007

@article{Tröger2019,
title = {Exploitation vs. Exploration - Computational temporal and semantic analysis explains semantic verbal fluency impairment in Alzheimer’s disease},
author = {Johannes Tr{\"o}ger and Nicklas Linz and Alexandra K{\"o}nig and Philippe Robert and Jan Alexandersson and Jessica Peter and Jutta Kray},
url = {https://www.sciencedirect.com/science/article/abs/pii/S0028393218305116?via%3Dihub},
doi = {https://doi.org/10.1016/j.neuropsychologia.2019.05.007},
year = {2019},
date = {2019},
journal = {Neuropsychologia},
pages = {53-61},
volume = {131},
abstract = {Impaired Semantic Verbal Fluency (SVF) in dementia due to Alzheimer's Disease (AD) and its precursor Mild Cognitive Impairment (MCI) is well known. Yet, it remains open whether this impairment mirrors the breakdown of semantic memory retrieval processes or executive control processes. Therefore, qualitative analysis of the SVF has been proposed but is limited in terms of methodology and feasibility in clinical practice. Consequently, research draws no conclusive picture which of these afore-mentioned processes drives the SVF impairment in AD and MCI. This study uses a qualitative computational approach - combining temporal and semantic information - to investigate exploitation and exploration patterns as indicators for semantic memory retrieval and executive control processes. Audio SVF recordings of 20 controls (C, 66-81 years), 55 MCI (57-94 years) and 20 AD subjects (66-82 years) were assessed while groups were matched according to age and education. All groups produced, on average, the same amount of semantically related items in rapid succession within word clusters. Conversely, towards AD, there was a clear decline in semantic as well as temporal exploration patterns between clusters. Results strongly point towards preserved exploitation - semantic memory retrieval processes - and hampered exploration - executive control processes - in AD and potentially in MCI.},
pubstate = {published},
type = {article}
}

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A controversial issue in psycholinguistics is the degree to which speakers employ audience design during language production. Hypothesising that a consideration of the listener’s needs is particularly relevant when the listener is under cognitive load, we had speakers describe objects for a listener performing an easy or a difficult simulated driving task. We predicted that speakers would introduce more redundancy in their descriptions in the difficult driving task, thereby accommodating the listener’s reduced cognitive capacity. The results showed that speakers did not adapt their descriptions to a change in the listener’s cognitive load. However, speakers who had experienced the driving task themselves before and who were presented with the difficult driving task first were more redundant than other speakers. These findings may suggest that speakers only consider the listener’s needs in the presence of strong enough cues, and do not update their beliefs about these needs during the task.

• https://www.tandfonline.com/doi/full/10.1080/23273798.2019.1648839
• https://doi.org/10.1080/23273798.2019.1648839

@article{Vogels2019,
title = {How speakers adapt object descriptions to listeners under load},
author = {Jorrig Vogels and David M. Howcroft and Elli Tourtouri and Vera Demberg},
url = {https://www.tandfonline.com/doi/full/10.1080/23273798.2019.1648839},
doi = {https://doi.org/10.1080/23273798.2019.1648839},
year = {2019},
date = {2019},
journal = {Language, Cognition and Neuroscience},
pages = {78-92},
publisher = {Routledge},
volume = {35},
number = {1},
abstract = {A controversial issue in psycholinguistics is the degree to which speakers employ audience design during language production. Hypothesising that a consideration of the listener’s needs is particularly relevant when the listener is under cognitive load, we had speakers describe objects for a listener performing an easy or a difficult simulated driving task. We predicted that speakers would introduce more redundancy in their descriptions in the difficult driving task, thereby accommodating the listener’s reduced cognitive capacity. The results showed that speakers did not adapt their descriptions to a change in the listener’s cognitive load. However, speakers who had experienced the driving task themselves before and who were presented with the difficult driving task first were more redundant than other speakers. These findings may suggest that speakers only consider the listener’s needs in the presence of strong enough cues, and do not update their beliefs about these needs during the task.},
pubstate = {published},
type = {article}
}

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While people process text, they make frequent use of information that is assumed to be common ground and left implicit in the text. One important type of such commonsense knowledge is script knowledge, which is the knowledge about the events and participants in everyday activities such as visiting a restaurant. Due to its implicitness, it is hard for machines to exploit such script knowledge for natural language processing (NLP). This dissertation addresses the role of script knowledge in a central field of NLP, natural language understanding (NLU). In the first part of this thesis, we address script parsing. The idea of script parsing is to align event and participant mentions in a text with an underlying script representation. This makes it possible for a system to leverage script knowledge for downstream tasks. We develop the first script parsing model for events that can be trained on a large scale on crowdsourced script data. The model is implemented as a linear-chain conditional random field and trained on sequences of short event descriptions, implicitly exploiting the inherent event ordering information. We show that this ordering information plays a crucial role for script parsing. Our model provides an important first step towards facilitating the use of script knowledge for NLU. In the second part of the thesis, we move our focus to an actual application in the area of NLU, i.e. machine comprehension. For the first time, we provide data sets for the systematic evaluation of the contribution of script knowledge for machine comprehension. We create MCScript, a corpus of narrations about everyday activities and questions on the texts. By collecting questions based on a scenario rather than a text, we aimed at creating challenging questions which require script knowledge for finding the correct answer. Based on the findings of a shared task carried out with the data set, which indicated that script knowledge is not relevant for good performance on our corpus, we revised the data collection process and created a second version of the data set.

• http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-313016
• https://doi.org/10.22028/D291-31301

@phdthesis{Ostermann2019,
title = {Script knowledge for natural language understanding},
author = {Simon Ostermann},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-313016},
doi = {https://doi.org/10.22028/D291-31301},
year = {2019},
date = {2019},
school = {Saarland University},
address = {Saarbruecken, Germany},
abstract = {While people process text, they make frequent use of information that is assumed to be common ground and left implicit in the text. One important type of such commonsense knowledge is script knowledge, which is the knowledge about the events and participants in everyday activities such as visiting a restaurant. Due to its implicitness, it is hard for machines to exploit such script knowledge for natural language processing (NLP). This dissertation addresses the role of script knowledge in a central field of NLP, natural language understanding (NLU). In the first part of this thesis, we address script parsing. The idea of script parsing is to align event and participant mentions in a text with an underlying script representation. This makes it possible for a system to leverage script knowledge for downstream tasks. We develop the first script parsing model for events that can be trained on a large scale on crowdsourced script data. The model is implemented as a linear-chain conditional random field and trained on sequences of short event descriptions, implicitly exploiting the inherent event ordering information. We show that this ordering information plays a crucial role for script parsing. Our model provides an important first step towards facilitating the use of script knowledge for NLU. In the second part of the thesis, we move our focus to an actual application in the area of NLU, i.e. machine comprehension. For the first time, we provide data sets for the systematic evaluation of the contribution of script knowledge for machine comprehension. We create MCScript, a corpus of narrations about everyday activities and questions on the texts. By collecting questions based on a scenario rather than a text, we aimed at creating challenging questions which require script knowledge for finding the correct answer. Based on the findings of a shared task carried out with the data set, which indicated that script knowledge is not relevant for good performance on our corpus, we revised the data collection process and created a second version of the data set.},
pubstate = {published},
type = {phdthesis}
}

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According to Grice’s (1975) theory of pragmatics, people tend to omit basic information when participating in a conversation (or writing a narrative) under the assumption that left out details are already known or can be inferred from commonsense knowledge by the hearer (or reader). Writing and understanding of texts makes particular use of a specific kind of common-sense knowledge, referred to as script knowledge. Schank and Abelson (1977) proposed Scripts as a model of human knowledge represented in memory that stores the frequent habitual activities, called scenarios, (e.g. eating in a fast food restaurant, etc.), and the different courses of action in those routines. This thesis addresses measures to provide a sound empirical basis for high-quality script models. We work on three key areas related to script modeling: script knowledge acquisition, script induction and script identification in text. We extend the existing repository of script knowledge bases in two different ways. First, we crowdsource a corpus of 40 scenarios with 100 event sequence descriptions (ESDs) each, thus going beyond the size of previous script collections. Second, the corpus is enriched with partial alignments of ESDs, done by human annotators. The crowdsourced partial alignments are used as prior knowledge to guide the semi-supervised script-induction algorithm proposed in this dissertation. We further present a semi-supervised clustering approach to induce script structure from crowdsourced descriptions of event sequences by grouping event descriptions into paraphrase sets and inducing their temporal order. The proposed semi-supervised clustering model better handles order variation in scripts and extends script representation formalism, Temporal Script graphs, by incorporating „arbitrary order“ equivalence classes in order to allow for the flexible event order inherent in scripts. In the third part of this dissertation, we introduce the task of scenario detection, in which we identify references to scripts in narrative texts. We curate a benchmark dataset of annotated narrative texts, with segments labeled according to the scripts they instantiate. The dataset is the first of its kind. The analysis of the annotation shows that one can identify scenario references in text with reasonable reliability. Subsequently, we proposes a benchmark model that automatically segments and identifies text fragments referring to given scenarios. The proposed model achieved promising results, and therefore opens up research on script parsing and wide coverage script acquisition.

• http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-301634
• https://doi.org/http://dx.doi.org/10.22028/D291-30163

@phdthesis{Wanzare2019,
title = {Script acquisition: a crowdsourcing and text mining approach},
author = {Lilian Diana Awuor Wanzare},
url = {http://nbn-resolving.de/urn:nbn:de:bsz:291--ds-301634},
doi = {https://doi.org/http://dx.doi.org/10.22028/D291-30163},
year = {2019},
date = {2019},
school = {Saarland University},
address = {Saarbruecken, Germany},
abstract = {According to Grice’s (1975) theory of pragmatics, people tend to omit basic information when participating in a conversation (or writing a narrative) under the assumption that left out details are already known or can be inferred from commonsense knowledge by the hearer (or reader). Writing and understanding of texts makes particular use of a specific kind of common-sense knowledge, referred to as script knowledge. Schank and Abelson (1977) proposed Scripts as a model of human knowledge represented in memory that stores the frequent habitual activities, called scenarios, (e.g. eating in a fast food restaurant, etc.), and the different courses of action in those routines. This thesis addresses measures to provide a sound empirical basis for high-quality script models. We work on three key areas related to script modeling: script knowledge acquisition, script induction and script identification in text. We extend the existing repository of script knowledge bases in two different ways. First, we crowdsource a corpus of 40 scenarios with 100 event sequence descriptions (ESDs) each, thus going beyond the size of previous script collections. Second, the corpus is enriched with partial alignments of ESDs, done by human annotators. The crowdsourced partial alignments are used as prior knowledge to guide the semi-supervised script-induction algorithm proposed in this dissertation. We further present a semi-supervised clustering approach to induce script structure from crowdsourced descriptions of event sequences by grouping event descriptions into paraphrase sets and inducing their temporal order. The proposed semi-supervised clustering model better handles order variation in scripts and extends script representation formalism, Temporal Script graphs, by incorporating "arbitrary order" equivalence classes in order to allow for the flexible event order inherent in scripts. In the third part of this dissertation, we introduce the task of scenario detection, in which we identify references to scripts in narrative texts. We curate a benchmark dataset of annotated narrative texts, with segments labeled according to the scripts they instantiate. The dataset is the first of its kind. The analysis of the annotation shows that one can identify scenario references in text with reasonable reliability. Subsequently, we proposes a benchmark model that automatically segments and identifies text fragments referring to given scenarios. The proposed model achieved promising results, and therefore opens up research on script parsing and wide coverage script acquisition.},
pubstate = {published},
type = {phdthesis}
}

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We introduce MCScript2.0, a machine comprehension corpus for the end-to-end evaluation of script knowledge. MCScript2.0 contains approx. 20,000 questions on approx. 3,500 texts, crowdsourced based on a new collection process that results in challenging questions. Half of the questions cannot be answered from the reading texts, but require the use of commonsense and, in particular, script knowledge. We give a thorough analysis of our corpus and show that while the task is not challenging to humans, existing machine comprehension models fail to perform well on the data, even if they make use of a commonsense knowledge base.

• https://www.aclweb.org/anthology/S19-1012

@inproceedings{ostermann2019mcscript2,
title = {MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants},
author = {Simon Ostermann and Michael Roth and Manfred Pinkal},
url = {https://www.aclweb.org/anthology/S19-1012},
year = {2019},
date = {2019-10-17},
booktitle = {Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (* SEM 2019)},
pages = {103-117},
abstract = {We introduce MCScript2.0, a machine comprehension corpus for the end-to-end evaluation of script knowledge. MCScript2.0 contains approx. 20,000 questions on approx. 3,500 texts, crowdsourced based on a new collection process that results in challenging questions. Half of the questions cannot be answered from the reading texts, but require the use of commonsense and, in particular, script knowledge. We give a thorough analysis of our corpus and show that while the task is not challenging to humans, existing machine comprehension models fail to perform well on the data, even if they make use of a commonsense knowledge base.},
pubstate = {published},
type = {inproceedings}
}

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Automatically generating globally coherent stories is a challenging problem. Neural text generation models have been shown to perform well at generating fluent sentences from data, but they usually fail to keep track of the overall coherence of the story after a couple of sentences. Existing work that incorporates a text planning module succeeded in generating recipes and dialogues, but appears quite data-demanding. We propose a novel story generation approach that generates globally coherent stories from a fairly small corpus. The model exploits a symbolic text planning module to produce text plans, thus reducing the demand of data; a neural surface realization module then generates fluent text conditioned on the text plan. Human evaluation showed that our model outperforms various baselines by a wide margin and generates stories which are fluent as well as globally coherent.

• https://aclanthology.org/W19-3404
• https://doi.org/10.18653/v1/W19-3404

@inproceedings{Fangzhou2019,
title = {A Hybrid Model for Globally Coherent Story Generation},
author = {Fangzhou Zhai and Vera Demberg and Pavel Shkadzko and Wei Shi and Asad Sayeed},
url = {https://aclanthology.org/W19-3404},
doi = {https://doi.org/10.18653/v1/W19-3404},
year = {2019},
date = {2019},
booktitle = {Proceedings of the Second Workshop on Storytelling},
pages = {34-45},
publisher = {Association for Computational Linguistics},
address = {Florence, Italy},
abstract = {Automatically generating globally coherent stories is a challenging problem. Neural text generation models have been shown to perform well at generating fluent sentences from data, but they usually fail to keep track of the overall coherence of the story after a couple of sentences. Existing work that incorporates a text planning module succeeded in generating recipes and dialogues, but appears quite data-demanding. We propose a novel story generation approach that generates globally coherent stories from a fairly small corpus. The model exploits a symbolic text planning module to produce text plans, thus reducing the demand of data; a neural surface realization module then generates fluent text conditioned on the text plan. Human evaluation showed that our model outperforms various baselines by a wide margin and generates stories which are fluent as well as globally coherent.},
pubstate = {published},
type = {inproceedings}
}

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The processing difficulty of each word we encounter in a sentence is affected by both our prior linguistic experience and our general knowledge about the world. Computational models of incremental language processing have, however, been limited in accounting for the influence of world knowledge.

We develop an incremental model of language comprehension that constructs – on a word-by-word basis – rich, probabilistic situation model representations. To quantify linguistic processing effort, we adopt Surprisal Theory, which asserts that the processing difficulty incurred by a word is inversely proportional to its expectancy (Hale, 2001; Levy, 2008). In contrast with typical language model implementations of surprisal, the proposed model instantiates a novel comprehension-centric metric of surprisal that reflects the likelihood of the unfolding utterance meaning as established after processing each word. Simulations are presented that demonstrate that linguistic experience and world knowledge are integrated in the model at the level of interpretation and combine in determining online expectations.

• Venhuizen2019ExpectationComprehension     (0.97MB)
• https://www.tandfonline.com/doi/full/10.1080/0163853X.2018.1448677
• https://doi.org/10.1080/0163853X.2018.1448677

@article{Venhuizen2019,
title = {Expectation-based Comprehension: Modeling the interaction of world knowledge and linguistic experience},
author = {Noortje Venhuizen and Matthew W. Crocker and Harm Brouwer},
url = {https://www.tandfonline.com/doi/full/10.1080/0163853X.2018.1448677},
doi = {https://doi.org/10.1080/0163853X.2018.1448677},
year = {2019},
date = {2019},
journal = {Discourse Processes},
pages = {229-255},
volume = {56},
number = {3},
abstract = {The processing difficulty of each word we encounter in a sentence is affected by both our prior linguistic experience and our general knowledge about the world. Computational models of incremental language processing have, however, been limited in accounting for the influence of world knowledge. We develop an incremental model of language comprehension that constructs - on a word-by-word basis - rich, probabilistic situation model representations. To quantify linguistic processing effort, we adopt Surprisal Theory, which asserts that the processing difficulty incurred by a word is inversely proportional to its expectancy (Hale, 2001; Levy, 2008). In contrast with typical language model implementations of surprisal, the proposed model instantiates a novel comprehension-centric metric of surprisal that reflects the likelihood of the unfolding utterance meaning as established after processing each word. Simulations are presented that demonstrate that linguistic experience and world knowledge are integrated in the model at the level of interpretation and combine in determining online expectations.},
pubstate = {published},
type = {article}
}

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The functional interpretation of two salient language-sensitive ERP components – the N400 and the P600 – remains a matter of debate. Prominent alternative accounts link the N400 to processes related to lexical retrieval, semantic integration, or both, while the P600 has been associated with syntactic reanalysis or, alternatively, to semantic integration. The often overlapping predictions of these competing accounts in extant experimental designs, however, has meant that previous findings have failed to clearly decide among them. Here, we present an experiment that directly tests the competing hypotheses using a design that clearly teases apart the retrieval versus integration view of the N400, while also dissociating a syntactic reanalysis/reprocessing account of the P600 from semantic integration. Our findings provide support for an integrated functional interpretation according to which the N400 reflects context-sensitive lexical retrieval – but not integration – processes. While the observed P600 effects were not predicted by any account, we argue that they can be reconciled with the integration view, if spatio-temporal overlap of ERP components is taken into consideration.

• delogu     (2.96MB)
• https://www.sciencedirect.com/science/article/pii/S0278262618304299
• https://doi.org/10.1016/j.bandc.2019.05.007

@article{delogu2019event,
title = {Event-related potentials index lexical retrieval (N400) and integration (P600) during language comprehension},
author = {Francesca Delogu and Harm Brouwer and Matthew W. Crocker},
url = {https://www.sciencedirect.com/science/article/pii/S0278262618304299},
doi = {https://doi.org/10.1016/j.bandc.2019.05.007},
year = {2019},
date = {2019},
journal = {Brain and Cognition},
volume = {135},
abstract = {The functional interpretation of two salient language-sensitive ERP components - the N400 and the P600 - remains a matter of debate. Prominent alternative accounts link the N400 to processes related to lexical retrieval, semantic integration, or both, while the P600 has been associated with syntactic reanalysis or, alternatively, to semantic integration. The often overlapping predictions of these competing accounts in extant experimental designs, however, has meant that previous findings have failed to clearly decide among them. Here, we present an experiment that directly tests the competing hypotheses using a design that clearly teases apart the retrieval versus integration view of the N400, while also dissociating a syntactic reanalysis/reprocessing account of the P600 from semantic integration. Our findings provide support for an integrated functional interpretation according to which the N400 reflects context-sensitive lexical retrieval - but not integration - processes. While the observed P600 effects were not predicted by any account, we argue that they can be reconciled with the integration view, if spatio-temporal overlap of ERP components is taken into consideration.},
pubstate = {published},
type = {article}
}

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Contrary to the Gricean maxims of quantity (Grice, in: Cole, Morgan (eds) Syntax and semantics: speech acts, vol III, pp 41-58, Academic Press, New York, 1975), it has been repeatedly shown that speakers often include redundant information in their utterances (over-specifications). Previous research on referential communication has long debated whether this redundancy is the result of speaker-internal or addressee-oriented processes, while it is also unclear whether referential redundancy hinders or facilitates comprehension.

We present an information-theoretic explanation for the use of over-specification in visually-situated communication, which quantifies the amount of uncertainty regarding the referent as entropy (Shannon in Bell Syst Tech J 5:10, https://doi.org/10.1002/j.1538-7305.1948.tb01338.x, 1948). Examining both the comprehension and production of over-specifications, we present evidence that (a) listeners’ processing is facilitated by the use of redundancy as well as by a greater reduction of uncertainty early on in the utterance, and (b) that at least for some speakers, listeners’ processing concerns influence their encoding of over-specifications: Speakers were more likely to use redundant adjectives when these adjectives reduced entropy to a higher degree than adjectives necessary for target identification.

• Rational-over-specification-in-visually-situated-comprehension-and-production     (1.72MB)
• https://link.springer.com/article/10.1007%2Fs41809-019-00032-6
• https://doi.org/10.1007/s41809-019-00032-6

@article{Tourtouri2019,
title = {Rational over-specification in visually-situated comprehension and production},
author = {Elli Tourtouri and Francesca Delogu and Les Sikos and Matthew W. Crocker},
url = {https://link.springer.com/article/10.1007%2Fs41809-019-00032-6},
doi = {https://doi.org/10.1007/s41809-019-00032-6},
year = {2019},
date = {2019},
journal = {Journal of Cultural Cognitive Science},
pages = {175-202},
volume = {3},
number = {2},
abstract = {Contrary to the Gricean maxims of quantity (Grice, in: Cole, Morgan (eds) Syntax and semantics: speech acts, vol III, pp 41-58, Academic Press, New York, 1975), it has been repeatedly shown that speakers often include redundant information in their utterances (over-specifications). Previous research on referential communication has long debated whether this redundancy is the result of speaker-internal or addressee-oriented processes, while it is also unclear whether referential redundancy hinders or facilitates comprehension. We present an information-theoretic explanation for the use of over-specification in visually-situated communication, which quantifies the amount of uncertainty regarding the referent as entropy (Shannon in Bell Syst Tech J 5:10, https://doi.org/10.1002/j.1538-7305.1948.tb01338.x, 1948). Examining both the comprehension and production of over-specifications, we present evidence that (a) listeners’ processing is facilitated by the use of redundancy as well as by a greater reduction of uncertainty early on in the utterance, and (b) that at least for some speakers, listeners’ processing concerns influence their encoding of over-specifications: Speakers were more likely to use redundant adjectives when these adjectives reduced entropy to a higher degree than adjectives necessary for target identification.},
pubstate = {published},
type = {article}
}

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We apply hyperbolic embeddings to trace the dynamics of change of conceptual-semantic relationships in a large diachronic scientific corpus (200 years). Our focus is on emerging scientific fields and the increasingly specialized terminology establishing around them. Reproducing high-quality hierarchical structures such as WordNet on a diachronic scale is a very difficult task.

Hyperbolic embeddings can map partial graphs into low dimensional, continuous hierarchical spaces, making more explicit the latent structure of the input. We show that starting from simple lists of word pairs (rather than a list of entities with directional links) it is possible to build diachronic hierarchical semantic spaces which allow us to model a process towards specialization for selected scientific fields.

• https://www.aclweb.org/anthology/W19-6106

@inproceedings{bizzoni-etal-2019-steps,
title = {Some steps towards the generation of diachronic WordNets},
author = {Yuri Bizzoni and Marius Mosbach and Dietrich Klakow and Stefania Degaetano-Ortlieb},
url = {https://www.aclweb.org/anthology/W19-6106},
year = {2019},
date = {2019-10-02},
booktitle = {Proceedings of the 22nd Nordic Conference on Computational Linguistics},
publisher = {Link{\"o}ping University Electronic Press},
address = {Turku, Finland},
abstract = {We apply hyperbolic embeddings to trace the dynamics of change of conceptual-semantic relationships in a large diachronic scientific corpus (200 years). Our focus is on emerging scientific fields and the increasingly specialized terminology establishing around them. Reproducing high-quality hierarchical structures such as WordNet on a diachronic scale is a very difficult task. Hyperbolic embeddings can map partial graphs into low dimensional, continuous hierarchical spaces, making more explicit the latent structure of the input. We show that starting from simple lists of word pairs (rather than a list of entities with directional links) it is possible to build diachronic hierarchical semantic spaces which allow us to model a process towards specialization for selected scientific fields.},
pubstate = {published},
type = {inproceedings}
}

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Languages may be differently distant from each other and their mutual intelligibility may be asymmetric. In this paper we introduce incom.py, a toolbox for calculating linguistic distances and asymmetries between related languages. incom.py allows linguist experts to quickly and easily perform statistical analyses and compare those with experimental results. We demonstrate the efficacy of incom.py in an incomprehension experiment on two Slavic languages: Bulgarian and Russian. Using incom.py we were able to validate three methods to measure linguistic distances and asymmetries: Levenshtein distance, word adaptation surprisal, and conditional entropy as predictors of success in a reading intercomprehension experiment.

• RANLP094     (0.63MB)
• https://aclanthology.org/R19-1094/
• https://doi.org/10.26615/978-954-452-056-4_094

@inproceedings{Mosbach2019,
title = {incom.py - A Toolbox for Calculating Linguistic Distances and Asymmetries between Related Languages},
author = {Marius Mosbach and Irina Stenger and Tania Avgustinova and Dietrich Klakow},
editor = {Galia Angelova and Ruslan Mitkov and Ivelina Nikolova and Irina Temnikova},
url = {https://aclanthology.org/R19-1094/},
doi = {https://doi.org/10.26615/978-954-452-056-4_094},
year = {2019},
date = {2019},
booktitle = {Proceedings of Recent Advances in Natural Language Processing, RANLP 2019, Varna, Bulgaria, 2-4 September 2019},
pages = {811-819},
address = {Varna, Bulgaria},
abstract = {Languages may be differently distant from each other and their mutual intelligibility may be asymmetric. In this paper we introduce incom.py, a toolbox for calculating linguistic distances and asymmetries between related languages. incom.py allows linguist experts to quickly and easily perform statistical analyses and compare those with experimental results. We demonstrate the efficacy of incom.py in an incomprehension experiment on two Slavic languages: Bulgarian and Russian. Using incom.py we were able to validate three methods to measure linguistic distances and asymmetries: Levenshtein distance, word adaptation surprisal, and conditional entropy as predictors of success in a reading intercomprehension experiment.},
pubstate = {published},
type = {inproceedings}
}

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This contribution outlines an international research effort for creating a typology of syntactic idioms on the borderline of the dictionary and the grammar. Recent studies focusing on the adequate description of such units, especially for modern Russian, have resulted in two types of linguistic resources: a microsyntactic dictionary of Russian, and a microsyntactically annotated corpus of Russian texts. Our goal now is to discover to what extent the findings can be generalized cross-linguistically in order to create analogous multilingual resources. The initial work consists in constructing a typology of relevant phenomena. The empirical base is provided by closely related languages which are mutually intelligible to various degrees. We start by creating an inventory for this typology for four representative Slavic languages: Russian (East Slavic), Bulgarian (South Slavic), Polish and Czech (West Slavic). Our preliminary results show that the aim is attainable and can be of relevance to theoretical, comparative and applied linguistics as well as in NLP tasks.

• https://link.springer.com/chapter/10.1007/978-3-030-30135-4_2

@inproceedings{Avgustinova2019,
title = {Towards a Typology of Microsyntactic Constructions},
author = {Tania Avgustinova and Leonid Iomdin},
editor = {Gloria Corpas-Pastor and Ruslan Mitkov},
url = {https://link.springer.com/chapter/10.1007/978-3-030-30135-4_2},
year = {2019},
date = {2019-09-18},
booktitle = {Computational and Corpus-Based Phraseology},
pages = {15-30},
publisher = {Springer, Cham},
abstract = {This contribution outlines an international research effort for creating a typology of syntactic idioms on the borderline of the dictionary and the grammar. Recent studies focusing on the adequate description of such units, especially for modern Russian, have resulted in two types of linguistic resources: a microsyntactic dictionary of Russian, and a microsyntactically annotated corpus of Russian texts. Our goal now is to discover to what extent the findings can be generalized cross-linguistically in order to create analogous multilingual resources. The initial work consists in constructing a typology of relevant phenomena. The empirical base is provided by closely related languages which are mutually intelligible to various degrees. We start by creating an inventory for this typology for four representative Slavic languages: Russian (East Slavic), Bulgarian (South Slavic), Polish and Czech (West Slavic). Our preliminary results show that the aim is attainable and can be of relevance to theoretical, comparative and applied linguistics as well as in NLP tasks.},
pubstate = {published},
type = {inproceedings}
}

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We present an approach for exploring the lexical choice patterns in translation on the basis of word embeddings. Specifically, we are interested in variation in translation according to translation mode, i.e. (written) translation vs. (simultaneous) interpreting. While it might seem obvious that the outputs of the two translation modes differ, there are hardly any accounts of the summative linguistic effects of one vs. the other. To explore such effects at the lexical level, we propose a data-driven approach: using neural word embeddings (Word2Vec), we compare the bilingual semantic spaces emanating from source-totranslation and source-to-interpreting.

• https://comparable.limsi.fr/bucc2019/Bizzoni_BUCC2019_paper1.pdf

@inproceedings{Bizzoni2019,
title = {Analyzing variation in translation through neural semantic spaces},
author = {Yuri Bizzoni and Elke Teich},
url = {https://comparable.limsi.fr/bucc2019/Bizzoni_BUCC2019_paper1.pdf},
year = {2019},
date = {2019-08-30},
booktitle = {Special topic: Neural Networks for Building and Using Comparable Corpora, Recent Advances in Natural Language Processing (RANLP), Varna, Bulgaria},
address = {Varna, Bulgaria},
abstract = {We present an approach for exploring the lexical choice patterns in translation on the basis of word embeddings. Specifically, we are interested in variation in translation according to translation mode, i.e. (written) translation vs. (simultaneous) interpreting. While it might seem obvious that the outputs of the two translation modes differ, there are hardly any accounts of the summative linguistic effects of one vs. the other. To explore such effects at the lexical level, we propose a data-driven approach: using neural word embeddings (Word2Vec), we compare the bilingual semantic spaces emanating from source-totranslation and source-to-interpreting.},
pubstate = {published},
type = {inproceedings}
}

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The perspective of being able to crowd-source coherence relations bears the promise of acquiring annotations for new texts quickly, which could then increase the size and variety of discourse-annotated corpora. It would also open the avenue to answering new research questions: Collecting annotations from a larger number of individuals per instance would allow to investigate the distribution of inferred relations, and to study individual differences in coherence relation interpretation. However, annotating coherence relations with untrained workers is not trivial. We here propose a novel two-step annotation procedure, which extends an earlier method by Scholman and Demberg (2017a). In our approach, coherence relation labels are inferred from connectives that workers insert into the text. We show that the proposed method leads to replicable coherence annotations, and analyse the agreement between the obtained relation labels and annotations from PDTB and RSTDT on the same texts.

• W19-4003     (0.34MB)
• https://aclanthology.org/W19-4003.pdf
• https://doi.org/10.22028/D291-30470

@inproceedings{Yung2019,
title = {Crowdsourcing Discourse Relation Annotations by a Two-Step Connective Insertion Task},
author = {Frances Pik Yu Yung and Merel Scholman and Vera Demberg},
editor = {Friedrich Annemarie and Zeyrek Deniz and Hoek Jet},
url = {https://aclanthology.org/W19-4003.pdf},
doi = {https://doi.org/10.22028/D291-30470},
year = {2019},
date = {2019-08-01},
isbn = {978-1-950737-38-3},
pages = {16-25},
publisher = {Linguistic Annotation Workshop at ACL. LAW XIII 2019},
address = {Stroudsburg, PA},
abstract = {The perspective of being able to crowd-source coherence relations bears the promise of acquiring annotations for new texts quickly, which could then increase the size and variety of discourse-annotated corpora. It would also open the avenue to answering new research questions: Collecting annotations from a larger number of individuals per instance would allow to investigate the distribution of inferred relations, and to study individual differences in coherence relation interpretation. However, annotating coherence relations with untrained workers is not trivial. We here propose a novel two-step annotation procedure, which extends an earlier method by Scholman and Demberg (2017a). In our approach, coherence relation labels are inferred from connectives that workers insert into the text. We show that the proposed method leads to replicable coherence annotations, and analyse the agreement between the obtained relation labels and annotations from PDTB and RSTDT on the same texts.},
pubstate = {published},
type = {inproceedings}
}

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Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language. As such, a considerable amount of research has sought to unify them, either by augmenting formal semantic systems with a distributional component, or by defining a formal system on top of distributed representations.

Arriving at such a unified framework has, however, proven extremely challenging. One reason for this is that formal and distributional semantics operate on a fundamentally different ‘representational currency’: formal semantics defines meaning in terms of models of the world, whereas distributional semantics defines meaning in terms of linguistic co-occurrence. Here, we pursue an alternative approach by deriving a vector space model that defines meaning in a distributed manner relative to formal models of the world.

We will show that the resulting Distributional Formal Semantics offers probabilistic distributed representations that are also inherently compositional, and that naturally capture quantification and entailment. We moreover show that, when used as part of a neural network model, these representations allow for capturing incremental meaning construction and probabilistic inferencing. This framework thus lays the groundwork for an integrated distributional and formal approach to meaning.

• https://link.springer.com/chapter/10.1007%2F978-3-662-59533-6_39
• https://doi.org/https://doi.org/10.1007/978-3-662-59533-6_39

@inproceedings{Venhuizen2019b,
title = {A Framework for Distributional Formal Semantics},
author = {Noortje Venhuizen and Petra Hendriks and Matthew W. Crocker and Harm Brouwer},
editor = {Rosalie Iemhoff and Michael Moortgat and Ruy de Queiroz},
url = {https://link.springer.com/chapter/10.1007%2F978-3-662-59533-6_39},
doi = {https://doi.org/https://doi.org/10.1007/978-3-662-59533-6_39},
year = {2019},
date = {2019-06-09},
booktitle = {Logic, Language, Information, and Computation, Proceedings of the 26th International Workshop WoLLIC 2019},
pages = {633-646},
abstract = {Formal semantics and distributional semantics offer complementary strengths in capturing the meaning of natural language. As such, a considerable amount of research has sought to unify them, either by augmenting formal semantic systems with a distributional component, or by defining a formal system on top of distributed representations. Arriving at such a unified framework has, however, proven extremely challenging. One reason for this is that formal and distributional semantics operate on a fundamentally different ‘representational currency’: formal semantics defines meaning in terms of models of the world, whereas distributional semantics defines meaning in terms of linguistic co-occurrence. Here, we pursue an alternative approach by deriving a vector space model that defines meaning in a distributed manner relative to formal models of the world. We will show that the resulting Distributional Formal Semantics offers probabilistic distributed representations that are also inherently compositional, and that naturally capture quantification and entailment. We moreover show that, when used as part of a neural network model, these representations allow for capturing incremental meaning construction and probabilistic inferencing. This framework thus lays the groundwork for an integrated distributional and formal approach to meaning.},
pubstate = {published},
type = {inproceedings}
}

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This paper deals with the automatic identification of literate and oral discourse in German texts. A range of linguistic features is selected and their role in distinguishing between literate- and oral-oriented registers is investigated, using a decision-tree classifier. It turns out that all of the investigated features are related in some way to oral conceptuality. Especially simple measures of complexity (average sentence and word length) are prominent indicators of oral and literate discourse. In addition, features of reference and deixis (realized by different types of pronouns) also prove to be very useful in determining the degree of orality of different registers

• vardial19_webVersion     (0.39MB)
• https://aclanthology.org/W19-1407/
• https://doi.org/10.18653/v1/W19-1407

@inproceedings{Ortmann2019,
title = {Variation between Different Discourse Types: Literate vs. Oral},
author = {Katrin Ortmann and Stefanie Dipper},
url = {https://aclanthology.org/W19-1407/},
doi = {https://doi.org/10.18653/v1/W19-1407},
year = {2019},
date = {2019-06-07},
booktitle = {In Proceedings of the NAACL-Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)},
pages = {64-79},
publisher = {Association for Computational Linguistics},
address = {Ann Arbor, Michigan},
abstract = {This paper deals with the automatic identification of literate and oral discourse in German texts. A range of linguistic features is selected and their role in distinguishing between literate- and oral-oriented registers is investigated, using a decision-tree classifier. It turns out that all of the investigated features are related in some way to oral conceptuality. Especially simple measures of complexity (average sentence and word length) are prominent indicators of oral and literate discourse. In addition, features of reference and deixis (realized by different types of pronouns) also prove to be very useful in determining the degree of orality of different registers},
pubstate = {published},
type = {inproceedings}
}

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