Publications

The abundance of temporal information in documents has lead to an increased interest in processing such information in the NLP community by considering temporal expressions. Besides domain-adaptation, acquiring knowledge on variation of temporal expressions according to time is relevant for improvement in automatic processing. So far, frequency-based accounts dominate in the investigation of specific temporal expressions. We present an approach to investigate diachronic changes of temporal expressions based on relative entropy – with the advantage of using conditioned probabilities rather than mere frequency. While we focus on scientific writing, our approach is generalizable to other domains and interesting not only in the field of NLP, but also in humanities.

• https://link.springer.com/chapter/10.1007/978-3-319-73706-5_22

@inproceedings{Degaetano-Ortlieb2018b,
title = {Diachronic variation of temporal expressions in scientific writing through the lens of relative entropy},
author = {Stefania Degaetano-Ortlieb and Jannik Str{\"o}tgen},
editor = {Georg Rehm and Thierry Declerck},
url = {https://link.springer.com/chapter/10.1007/978-3-319-73706-5_22},
year = {2018},
date = {2018},
booktitle = {Language Technologies for the Challenges of the Digital Age: 27th International Conference, GSCL 2017, September 13-14, Proceedings. Lecture Notes in Computer Science},
pages = {250-275},
publisher = {Springer International Publishing},
address = {Berlin, Germany},
abstract = {The abundance of temporal information in documents has lead to an increased interest in processing such information in the NLP community by considering temporal expressions. Besides domain-adaptation, acquiring knowledge on variation of temporal expressions according to time is relevant for improvement in automatic processing. So far, frequency-based accounts dominate in the investigation of specific temporal expressions. We present an approach to investigate diachronic changes of temporal expressions based on relative entropy – with the advantage of using conditioned probabilities rather than mere frequency. While we focus on scientific writing, our approach is generalizable to other domains and interesting not only in the field of NLP, but also in humanities.},
pubstate = {published},
type = {inproceedings}
}

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We present an approach to detect stylistic variation across social variables (here: gender and social class), considering also diachronic change in language use. For detection of stylistic variation, we use relative entropy, measuring the difference between probability distributions at different linguistic levels (here: lexis and grammar). In addition, by relative entropy, we can determine which linguistic units are related to stylistic variation.

• naaclhlt2018-degaetano     (0.54MB)
• https://aclanthology.org/W18-1601
• https://doi.org/10.18653/v1/W18-1601

@inproceedings{Degaetano-Ortlieb2018,
title = {Stylistic Variation over 200 Years of Court. Proceedings According to Gender and Social Class},
author = {Stefania Degaetano-Ortlieb},
url = {https://aclanthology.org/W18-1601},
doi = {https://doi.org/10.18653/v1/W18-1601},
year = {2018},
date = {2018},
booktitle = {Proceedings of the 2nd Workshop on Stylistic Variation collocated with NAACL HLT 2018, June 1-6. ACL},
pages = {1-10},
publisher = {Association for Computational Linguistics},
address = {New Orleans},
abstract = {We present an approach to detect stylistic variation across social variables (here: gender and social class), considering also diachronic change in language use. For detection of stylistic variation, we use relative entropy, measuring the difference between probability distributions at different linguistic levels (here: lexis and grammar). In addition, by relative entropy, we can determine which linguistic units are related to stylistic variation.},
pubstate = {published},
type = {inproceedings}
}

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In the digital humanities, topic models are a widely applied text mining method (Meeks and Weingart, 2012). While their use for mining literary texts is not entirely straightforward (Schmidt, 2012), there is ample evidence for their use on factual text (e.g. Au Yeung and Jatowt, 2011; Thompson et al., 2016). We present an approach for exploring the research fields of selected authors in a corpus of late modern scientific English by topic modelling, looking at the topics assigned to an author’s texts over the author’s lifetime. Areas of applications we target are history of science, where we may be interested in the evolution of scientific disciplines over time (Thompson et al., 2016; Fankhauser et al., 2016), or diachronic linguistics, where we may be interested in the formation of languages for specific purposes (LSP) or specific scientific “styles” (cf. Bazerman, 1988; Degaetano-Ortlieb and Teich, 2016). We use the Royal Society Corpus (RSC, Kermes et al., 2016), which is based on the first two centuries (1665–1869) of the Philosophical Transactions and the Proceedings of the Royal Society of London. The corpus contains 9,779 texts (32 million tokens) and is available at https://fedora.clarin-d.uni-saarland.de/rsc/. As we are interested in the development of individual authors, we focus on the single-author texts (81%) of the corpus. In total, 2,752 names are annotated in the single-author papers, but the activity of authors varies. Figure 1 shows that a small group of authors wrote a large portion of the texts. In fact, the twelve authors used for our analysis wrote 11% of the single-author articles.

• https://dh2018.adho.org/en/using-topic-modelling-to-explore-authors-research-fields-in-a-corpus-of-historical-scientific-english/

@inproceedings{fischer-etal2018,
title = {Using Topic Modelling to Explore Authors’ Research Fields in a Corpus of Historical Scientific English},
author = {Stefan Fischer and J{\"o}rg Knappen and Elke Teich},
url = {https://dh2018.adho.org/en/using-topic-modelling-to-explore-authors-research-fields-in-a-corpus-of-historical-scientific-english/},
year = {2018},
date = {2018},
booktitle = {Proceedings of DH 2018},
address = {Mexico City, Mexico},
abstract = {In the digital humanities, topic models are a widely applied text mining method (Meeks and Weingart, 2012). While their use for mining literary texts is not entirely straightforward (Schmidt, 2012), there is ample evidence for their use on factual text (e.g. Au Yeung and Jatowt, 2011; Thompson et al., 2016). We present an approach for exploring the research fields of selected authors in a corpus of late modern scientific English by topic modelling, looking at the topics assigned to an author’s texts over the author’s lifetime. Areas of applications we target are history of science, where we may be interested in the evolution of scientific disciplines over time (Thompson et al., 2016; Fankhauser et al., 2016), or diachronic linguistics, where we may be interested in the formation of languages for specific purposes (LSP) or specific scientific “styles” (cf. Bazerman, 1988; Degaetano-Ortlieb and Teich, 2016). We use the Royal Society Corpus (RSC, Kermes et al., 2016), which is based on the first two centuries (1665–1869) of the Philosophical Transactions and the Proceedings of the Royal Society of London. The corpus contains 9,779 texts (32 million tokens) and is available at https://fedora.clarin-d.uni-saarland.de/rsc/. As we are interested in the development of individual authors, we focus on the single-author texts (81%) of the corpus. In total, 2,752 names are annotated in the single-author papers, but the activity of authors varies. Figure 1 shows that a small group of authors wrote a large portion of the texts. In fact, the twelve authors used for our analysis wrote 11% of the single-author articles.},
pubstate = {published},
type = {inproceedings}
}

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Referential gaze has been shown to benefit language processing in situated communication in terms of shifting visual attention and leading to shorter reaction times on subsequent tasks. The present study simultaneously assessed both visual attention and, importantly, the immediate cogni-tive load induced at different stages of sentence processing. We aimed to examine the dynamics of combining visual and linguistic information in creating anticipation for a specific object and the effect this has on language processing. We report evidence from three visual-world eye-tracking experiments, showing that referential gaze leads to a shift in visual attention toward the cued object, which consequently lowers the effort required for processing the linguistic reference. 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.

• https://onlinelibrary.wiley.com/doi/full/10.1111/cogs.12682
• https://doi.org/10.1111/cogs.12682

@article{ Sekicki2018,
title = {Eye'll help you out! How the gaze cue reduces the cognitive load required for reference processing},
author = {Mirjana Sekicki and Maria Staudte},
url = {https://onlinelibrary.wiley.com/doi/full/10.1111/cogs.12682},
doi = {https://doi.org/10.1111/cogs.12682},
year = {2018},
date = {2018},
journal = {Cognitive Science},
pages = {1-40},
volume = {42},
abstract = {Referential gaze has been shown to benefit language processing in situated communication in terms of shifting visual attention and leading to shorter reaction times on subsequent tasks. The present study simultaneously assessed both visual attention and, importantly, the immediate cogni-tive load induced at different stages of sentence processing. We aimed to examine the dynamics of combining visual and linguistic information in creating anticipation for a specific object and the effect this has on language processing. We report evidence from three visual-world eye-tracking experiments, showing that referential gaze leads to a shift in visual attention toward the cued object, which consequently lowers the effort required for processing the linguistic reference. 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.},
pubstate = {published},
type = {article}
}

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@miscellaneous{Ankener2018b,
title = {Visually informed prediction: How combining lexical and visual information affects surprisal},
author = {Maria Staudte and Christine Ankener},
year = {2018},
date = {2018-10-17},
booktitle = {31st Annual Conference on Sentence Processing (CUNY)},
address = {UC Davis, USA},
pubstate = {published},
type = {miscellaneous}
}

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@inproceedings{Sekicki2018c,
title = {Reference resolution and the integration of referential visual cues},
author = {Maria Staudte andMirjana Sekicki},
year = {2018},
date = {2018-10-17},
booktitle = {SSLP (pre-AMLaP) workshop 2018},
address = {Berlin, Germany},
pubstate = {published},
type = {inproceedings}
}

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Gaze Cues in face-to-face interactions

• Speakers‘ direct their gaze toward an object approximately 800ms before mentioning. (Griffin & Bock, 2000)
• Previous studies showed that listeners utilize speakers‘ gaze to form predictions about the unfolding sentence. (Jachmann et al., 2017)
• Do listeners utilize this external cue to validate expectations about the unfolding sentence? And, if so, how does this effect the comprehension of the noun?

• https://www.researchgate.net/publication/327623334_DISCONFIRMATION_OF_LINGUISTIC_PREDICTION_BY_NON-LINGUISTIC_CUES

@miscellaneous{Jachmann2018,
title = {(Dis-)confirmation of linguistic prediction by non-linguistic cues},
author = {Torsten Jachmann and Heiner Drenhaus and Maria Staudte and Matthew W. Crocker},
url = {https://www.researchgate.net/publication/327623334_DISCONFIRMATION_OF_LINGUISTIC_PREDICTION_BY_NON-LINGUISTIC_CUES},
year = {2018},
date = {2018},
booktitle = {24th Annual Conference on Architectures and Mechanisms for Language Processing (AMLaP)},
address = {Berlin},
abstract = {Gaze Cues in face-to-face interactions

• Speakers‘ direct their gaze toward an object approximately 800ms before mentioning. (Griffin & Bock, 2000)
• Previous studies showed that listeners utilize speakers‘ gaze to form predictions about the unfolding sentence. (Jachmann et al., 2017)
• Do listeners utilize this external cue to validate expectations about the unfolding sentence? And, if so, how does this effect the comprehension of the noun?

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@inproceedings{Sekicki2018,
title = {Visual cues and the graded reduction of referential uncertainty},
author = {Maria Staudte andMirjana Sekicki},
year = {2018},
date = {2018-10-17},
booktitle = {24th Annual Conference on Architectures and Mechanisms for Language Processing (AMLaP)},
address = {Berlin},
pubstate = {published},
type = {inproceedings}
}

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Referential gaze has been shown to benefit language processing in situated communication in terms of shifting visual attention and leading to shorter reaction times on subsequent tasks. The present study simultaneously assessed both visual attention and, importantly, the immediate cognitive load induced at different stages of sentence processing.

We aimed to examine the dynamics of combining visual and linguistic information in creating anticipation for a specific object and the effect this has on language processing. We report evidence from three visual‐world eye‐tracking experiments, showing that referential gaze leads to a shift in visual attention toward the cued object, which consequently lowers the effort required for processing the linguistic reference.

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.

• https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6585668/
• https://doi.org/10.1111/cogs.12682

@article{Sekicki2018c,
title = {Eye’ll help you out! How the gaze cue reduces the cognitive load required for reference processing},
author = {Maria Staudte andMirjana Sekicki},
url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6585668/},
doi = {https://doi.org/10.1111/cogs.12682},
year = {2018},
date = {2018-10-17},
journal = {Cognitive science},
pages = {2418-2458},
volume = {42},
number = {8},
abstract = {Referential gaze has been shown to benefit language processing in situated communication in terms of shifting visual attention and leading to shorter reaction times on subsequent tasks. The present study simultaneously assessed both visual attention and, importantly, the immediate cognitive load induced at different stages of sentence processing. We aimed to examine the dynamics of combining visual and linguistic information in creating anticipation for a specific object and the effect this has on language processing. We report evidence from three visual‐world eye‐tracking experiments, showing that referential gaze leads to a shift in visual attention toward the cued object, which consequently lowers the effort required for processing the linguistic reference. 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.},
pubstate = {published},
type = {article}
}

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Speakers tend to fixate objects they are about to mention, while listeners inspect those objects that they believe to be intended referents of the speaker. These production- and comprehension-contingent gaze behaviors may form an integral part of the signal itself, making it inherently reciprocal.

Here, we present work that has investigated the interplay of gaze and language and assessed the role of speaker gaze for language comprehension as well as the utility of listener gaze for an instruction giver. Both lines of research make use of artificial interaction partners which increases experimental control while maintaining a dynamic interactive setting. Thus, the reciprocal nature of situated dialogue becomes a tractable aspect in the enterprise of dealing with human (gaze) behavior.

• https://benjamins.com/catalog/ais.10.05sta
• https://doi.org/10.1075/ais.10.05sta

@incollection{Staudte2018,
title = {On the role of gaze for successful and efficient communication},
author = {Maria Staudte and Matthew W. Crocker},
url = {https://benjamins.com/catalog/ais.10.05sta},
doi = {https://doi.org/10.1075/ais.10.05sta},
year = {2018},
date = {2018-10-17},
booktitle = {Eye-tracking in Interaction: Studies on the role of eye gaze in dialogue},
publisher = {John Benjamins Publishing Company},
abstract = {Speakers tend to fixate objects they are about to mention, while listeners inspect those objects that they believe to be intended referents of the speaker. These production- and comprehension-contingent gaze behaviors may form an integral part of the signal itself, making it inherently reciprocal. Here, we present work that has investigated the interplay of gaze and language and assessed the role of speaker gaze for language comprehension as well as the utility of listener gaze for an instruction giver. Both lines of research make use of artificial interaction partners which increases experimental control while maintaining a dynamic interactive setting. Thus, the reciprocal nature of situated dialogue becomes a tractable aspect in the enterprise of dealing with human (gaze) behavior.},
pubstate = {published},
type = {incollection}
}

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A word’s predictability or surprisal, as determined by cloze probabilities or language models (Frank, 2013) is related to processing effort, in that less expected words take more effort to process (Hale, 2001; Lau et al., 2013).

A word’s surprisal, however, may also be influenced by the non-linguistic context, such as visual cues: 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). How visual context affects surprisal and processing effort, however, remains unclear.

Here, we present a series of four studies providing evidence on how visually-determined probabilistic expectations for a spoken target word, as indicated by anticipatory eye movements, predict graded processing effort for that word, as assessed by a pupillometric measure (the Index of Cognitive Activity, ICA). These findings are a clear and robust demonstration that the non-linguistic context can immediately influence both lexical expectations, and surprisal-based processing effort.

• https://www.frontiersin.org/articles/10.3389/fpsyg.2018.02387/full
• https://doi.org/10.3389/fpsyg.2018.02387

@article{Ankener2018b,
title = {The Influence of Visual Uncertainty on Word Surprisal and Processing Effort},
author = {Maria Staudte andMirjana Sekicki and Christine Ankener},
url = {https://www.frontiersin.org/articles/10.3389/fpsyg.2018.02387/full},
doi = {https://doi.org/10.3389/fpsyg.2018.02387},
year = {2018},
date = {2018-10-17},
journal = {Frontiers in Psychology},
pages = {2387},
volume = {9},
abstract = {A word’s predictability or surprisal, as determined by cloze probabilities or language models (Frank, 2013) is related to processing effort, in that less expected words take more effort to process (Hale, 2001; Lau et al., 2013). A word’s surprisal, however, may also be influenced by the non-linguistic context, such as visual cues: 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). How visual context affects surprisal and processing effort, however, remains unclear. Here, we present a series of four studies providing evidence on how visually-determined probabilistic expectations for a spoken target word, as indicated by anticipatory eye movements, predict graded processing effort for that word, as assessed by a pupillometric measure (the Index of Cognitive Activity, ICA). These findings are a clear and robust demonstration that the non-linguistic context can immediately influence both lexical expectations, and surprisal-based processing effort.},
pubstate = {published},
type = {article}
}

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• https://doi.org/10.3389/fpsyg.2018.02276
• https://doi.org/10.3389/fpsyg.2018.02276

@article{Vogels2018,
title = {The index of cognitive activity as a measure of cognitive processing load in dual task settings},
author = {Jorrig Vogels and Vera Demberg and Jutta Kray},
url = {https://doi.org/10.3389/fpsyg.2018.02276},
doi = {https://doi.org/10.3389/fpsyg.2018.02276},
year = {2018},
date = {2018},
journal = {Frontiers in Psychololgy},
pages = {2276},
volume = {9},
abstract = {

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• https://pubmed.ncbi.nlm.nih.gov/30550333/
• https://doi.org/10.1037/pag0000316

@article{Häuser2018,
title = {Surprisal modulates dual-task performance in older adults: Pupillometry shows age-related trade-offs in task performance and time-course of language processing},
author = {Katja H{\"a}user and Vera Demberg and Jutta Kray},
url = {https://pubmed.ncbi.nlm.nih.gov/30550333/},
doi = {https://doi.org/10.1037/pag0000316},
year = {2018},
date = {2018-10-17},
journal = {Psychology and Aging},
pages = {1168-1180},
volume = {33},
number = {8},
abstract = {

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Developing conventional natural language generation systems requires extensive attention from human experts in order to craft complex sets of sentence planning rules. We propose a Bayesian nonparametric approach to learn sentence planning rules by inducing synchronous tree substitution grammars for pairs of text plans and morphosyntactically-specified dependency trees. Our system is able to learn rules which can be used to generate novel texts after training on small datasets.

• https://aclanthology.org/W18-6546
• https://doi.org/10.18653/v1/W18-6546

@inproceedings{Howcroft2018,
title = {Toward Bayesian Synchronous Tree Substitution Grammars for Sentence Planning},
author = {David M. Howcroft and Dietrich Klakow and Vera Demberg},
url = {https://aclanthology.org/W18-6546},
doi = {https://doi.org/10.18653/v1/W18-6546},
year = {2018},
date = {2018},
booktitle = {Proceedings of the 11th International Conference on Natural Language Generation},
pages = {391-396},
publisher = {Association for Computational Linguistics},
address = {Tilburg, The Netherlands},
abstract = {Developing conventional natural language generation systems requires extensive attention from human experts in order to craft complex sets of sentence planning rules. We propose a Bayesian nonparametric approach to learn sentence planning rules by inducing synchronous tree substitution grammars for pairs of text plans and morphosyntactically-specified dependency trees. Our system is able to learn rules which can be used to generate novel texts after training on small datasets.},
pubstate = {published},
type = {inproceedings}
}

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Human world knowledge contains information about prototypical events and their participants and locations. In this paper, we train the first models using multi-task learning that can both predict missing event participants and also perform semantic role classification based on semantic plausibility. Our best-performing model is an improvement over the previous state-of-the-art on thematic fit modelling tasks. The event embeddings learned by the model can additionally be used effectively in an event similarity task, also outperforming the state-of-the-art.

• https://aclanthology.org/S18-2002
• https://doi.org/10.18653/v1/S18-2002

@inproceedings{Hong2018,
title = {Learning Distributed Event Representations with a Multi-Task Approach},
author = {Xudong Hong and Asad Sayeed and Vera Demberg},
url = {https://aclanthology.org/S18-2002},
doi = {https://doi.org/10.18653/v1/S18-2002},
year = {2018},
date = {2018},
booktitle = {Proceedings of the Seventh Joint Conference on Lexical and Computational Semantics},
pages = {11-21},
publisher = {Association for Computational Linguistics},
address = {New Orleans, USA},
abstract = {Human world knowledge contains information about prototypical events and their participants and locations. In this paper, we train the first models using multi-task learning that can both predict missing event participants and also perform semantic role classification based on semantic plausibility. Our best-performing model is an improvement over the previous state-of-the-art on thematic fit modelling tasks. The event embeddings learned by the model can additionally be used effectively in an event similarity task, also outperforming the state-of-the-art.},
pubstate = {published},
type = {inproceedings}
}

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Commonsense knowledge as provided by scripts is crucially relevant for text understanding systems, providing a basis for commonsense inference. This paper considers a relevant subtask of script-based text understanding, the task of mapping event mentions in a text to script events. We focus on script representations where events are associated with paraphrase sets, i.e. sets of crowdsourced event descriptions. We provide a detailed annotation of event mention/description pairs with textual entailment types. We demonstrate that representing events in terms of paraphrase sets can massively improve the performance of text-to-script mapping systems. However, for a residual substantial fraction of cases, deeper inference is still required.

• https://www.semanticscholar.org/paper/Mapping-Texts-to-Scripts%3A-An-Entailment-Study-Ostermann-Seitz/7970ec54afb3d78d9f061a38db27d0bd19e215d5

@inproceedings{MCScriptb,
title = {Mapping Text to Scripts: An Entailment Study},
author = {Simon Ostermann and Hannah Seitz and Stefan Thater and Manfred Pinkal},
url = {https://www.semanticscholar.org/paper/Mapping-Texts-to-Scripts%3A-An-Entailment-Study-Ostermann-Seitz/7970ec54afb3d78d9f061a38db27d0bd19e215d5},
year = {2018},
date = {2018},
booktitle = {Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC 2018)},
address = {Miyazaki, Japan},
abstract = {Commonsense knowledge as provided by scripts is crucially relevant for text understanding systems, providing a basis for commonsense inference. This paper considers a relevant subtask of script-based text understanding, the task of mapping event mentions in a text to script events. We focus on script representations where events are associated with paraphrase sets, i.e. sets of crowdsourced event descriptions. We provide a detailed annotation of event mention/description pairs with textual entailment types. We demonstrate that representing events in terms of paraphrase sets can massively improve the performance of text-to-script mapping systems. However, for a residual substantial fraction of cases, deeper inference is still required.},
pubstate = {published},
type = {inproceedings}
}

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We introduce a large dataset of narrative texts and questions about these texts, intended to be used in a machine comprehension task that requires reasoning using commonsense knowledge. Our dataset complements similar datasets in that we focus on stories about everyday activities, such as going to the movies or working in the garden, and that the questions require commonsense knowledge, or more specifically, script knowledge, to be answered. We show that our mode of data collection via crowdsourcing results in a substantial amount of such inference questions. The dataset forms the basis of a shared task on commonsense and script knowledge organized at SemEval 2018 and provides challenging test cases for the broader natural language understanding community

• https://aclanthology.org/L18-1564"

@inproceedings{MCScript,
title = {MCScript: A Novel Dataset for Assessing Machine Comprehension Using Script Knowledge},
author = {Michael Roth and Stefan Thater andSimon Ostermann and Ashutosh Modi and Manfred Pinkal},
url = {https://aclanthology.org/L18-1564"},
year = {2018},
date = {2018},
booktitle = {Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC 2018)},
publisher = {European Language Resources Association (ELRA)},
address = {Miyazaki, Japan},
abstract = {We introduce a large dataset of narrative texts and questions about these texts, intended to be used in a machine comprehension task that requires reasoning using commonsense knowledge. Our dataset complements similar datasets in that we focus on stories about everyday activities, such as going to the movies or working in the garden, and that the questions require commonsense knowledge, or more specifically, script knowledge, to be answered. We show that our mode of data collection via crowdsourcing results in a substantial amount of such inference questions. The dataset forms the basis of a shared task on commonsense and script knowledge organized at SemEval 2018 and provides challenging test cases for the broader natural language understanding community},
pubstate = {published},
type = {inproceedings}
}

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This report summarizes the results of the SemEval 2018 task on machine comprehension using commonsense knowledge. For this machine comprehension task, we created a new corpus, MCScript. It contains a high number of questions that require commonsense knowledge for finding the correct answer. 11 teams from 4 different countries participated in this shared task, most of them used neural approaches. The best performing system achieves an accuracy of 83.95%, outperforming the baselines by a large margin, but still far from the human upper bound, which was found to be at 98%.

• https://aclanthology.org/S18-1119
• https://doi.org/10.18653/v1/S18-1119

@inproceedings{SemEval2018Task11,
title = {SemEval-2018 Task 11: Machine Comprehension using Commonsense Knowledge},
author = {Michael Roth and Stefan Thater andSimon Ostermann and Ashutosh Modi and Manfred Pinkal},
url = {https://aclanthology.org/S18-1119},
doi = {https://doi.org/10.18653/v1/S18-1119},
year = {2018},
date = {2018},
booktitle = {Proceedings of the 12th International Workshop on Semantic Evaluation},
pages = {747-757},
publisher = {Association for Computational Linguistics},
address = {New Orleans, Louisiana},
abstract = {This report summarizes the results of the SemEval 2018 task on machine comprehension using commonsense knowledge. For this machine comprehension task, we created a new corpus, MCScript. It contains a high number of questions that require commonsense knowledge for finding the correct answer. 11 teams from 4 different countries participated in this shared task, most of them used neural approaches. The best performing system achieves an accuracy of 83.95%, outperforming the baselines by a large margin, but still far from the human upper bound, which was found to be at 98%.},
pubstate = {published},
type = {inproceedings}
}

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When reading a text describing an everyday activity, comprehenders build a model of the situation described that includes prior knowledge of the entities, locations, and sequences of actions that typically occur within the event. Previous work has demonstrated that such knowledge guides the processing of incoming information by making event boundaries more or less expected.

In the present ERP study, we investigated whether comprehenders’ expectations about event boundaries are influenced by how elaborately common events are described in the context. Participants read short stories in which a common activity (e.g., washing the dishes) was described either in brief or in an elaborate manner. The final sentence contained a target word referring to a more predictable action marking a fine event boundary (e.g., drying) or a less predictable action, marking a coarse event boundary (e.g., jogging). The results revealed a larger N400 effect for coarse event boundaries compared to fine event boundaries, but no interaction with description length. Between 600 and 1000 ms, however, elaborate contexts elicited a larger frontal positivity compared to brief contexts.

This effect was largely driven by less predictable targets, marking coarse event boundaries. We interpret the P600 effect as indexing the updating of the situation model at event boundaries, consistent with Event Segmentation Theory (EST). The updating process is more demanding with coarse event boundaries, which presumably require the construction of a new situation model. Electronic supplementary material The online version of this article (10.3758/s13421-017-0766-4) contains supplementary material, which is available to authorized users.

• On-the-predictability-of-event-boundaries-in-discourse     (0.73MB)
• https://www.researchgate.net/publication/321175597_On_the_predictability_of_event_boundaries_in_discourse_An_ERP_investigation
• https://doi.org/https://doi.org/10.3758/s13421-017-0766-4

@article{Delogu2018,
title = {On the predictability of event-boundaries in discourse: an ERP investigation},
author = {Francesca Delogu and Heiner Drenhaus and Matthew W. Crocker},
url = {https://www.researchgate.net/publication/321175597_On_the_predictability_of_event_boundaries_in_discourse_An_ERP_investigation},
doi = {https://doi.org/https://doi.org/10.3758/s13421-017-0766-4},
year = {2018},
date = {2018},
journal = {Memory and Cognition},
pages = {315-325},
volume = {46},
number = {2},
abstract = {When reading a text describing an everyday activity, comprehenders build a model of the situation described that includes prior knowledge of the entities, locations, and sequences of actions that typically occur within the event. Previous work has demonstrated that such knowledge guides the processing of incoming information by making event boundaries more or less expected. In the present ERP study, we investigated whether comprehenders’ expectations about event boundaries are influenced by how elaborately common events are described in the context. Participants read short stories in which a common activity (e.g., washing the dishes) was described either in brief or in an elaborate manner. The final sentence contained a target word referring to a more predictable action marking a fine event boundary (e.g., drying) or a less predictable action, marking a coarse event boundary (e.g., jogging). The results revealed a larger N400 effect for coarse event boundaries compared to fine event boundaries, but no interaction with description length. Between 600 and 1000 ms, however, elaborate contexts elicited a larger frontal positivity compared to brief contexts. This effect was largely driven by less predictable targets, marking coarse event boundaries. We interpret the P600 effect as indexing the updating of the situation model at event boundaries, consistent with Event Segmentation Theory (EST). The updating process is more demanding with coarse event boundaries, which presumably require the construction of a new situation model. Electronic supplementary material The online version of this article (10.3758/s13421-017-0766-4) contains supplementary material, which is available to authorized users.},
pubstate = {published},
type = {article}
}

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A word’s predictability or surprisal, as determined by cloze probabilities or language models (e.g. Frank, Otten, Galli, & Vigliocco, 2015) is related to processing effort, in that less expected words take more effort to process (e.g. Hale, 2001). A words surprisal, however, may also be influenced by the non-linguistic context, such as visual cues: In the visual world paradigm (VWP), for example, anticipatory eye movements suggest that comprehenders exploit the scene to predict what will be mentioned next (Altmann & Kamide, 1999).

How visual context affects word surprisal and processing effort, however, remains unclear. Here, we present evidence that visually-determined probabilistic expectations for a spoken target word predict graded processing effort for that word, in both pupillometric (ICA) and ERP (N400) measures. These findings demonstrate that the non-linguistic context can immediately influence both lexical expectations, and surprisal-based processing effort.

• https://www.researchgate.net/publication/325644935_Multimodal_Surprisal_in_the_N400_and_the_Index_of_Cognitive_Activity

@inproceedings{Ankener2018,
title = {Multimodal Surprisal in the N400 and the Index of Cognitive Activity},
author = {Christine Ankener and Heiner Drenhaus and Matthew W. Crocker and Maria Staudte},
url = {https://www.researchgate.net/publication/325644935_Multimodal_Surprisal_in_the_N400_and_the_Index_of_Cognitive_Activity},
year = {2018},
date = {2018},
booktitle = {Proceedings of the 40th Annual Cognitive Science Society Meeting},
pages = {94-100},
publisher = {The Cognitive Science Society},
address = {Madison, Wisconsin},
abstract = {A word’s predictability or surprisal, as determined by cloze probabilities or language models (e.g. Frank, Otten, Galli, & Vigliocco, 2015) is related to processing effort, in that less expected words take more effort to process (e.g. Hale, 2001). A words surprisal, however, may also be influenced by the non-linguistic context, such as visual cues: In the visual world paradigm (VWP), for example, anticipatory eye movements suggest that comprehenders exploit the scene to predict what will be mentioned next (Altmann & Kamide, 1999). How visual context affects word surprisal and processing effort, however, remains unclear. Here, we present evidence that visually-determined probabilistic expectations for a spoken target word predict graded processing effort for that word, in both pupillometric (ICA) and ERP (N400) measures. These findings demonstrate that the non-linguistic context can immediately influence both lexical expectations, and surprisal-based processing effort.},
pubstate = {published},
type = {inproceedings}
}

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