Publications

In this paper, we present Roleo, a web tool for visualizing the vector spaces generated by the evaluation of distributional memory (DM) models over thematic fit judgements. A thematic fit judgement is a rating of the selectional preference of a verb for an argument that fills a given thematic role. The DM approach to thematic fit judgements involves the construction of a sub-space in which a prototypical role-filler can be built for comparison to the noun being judged. We describe a publicly-accessible web tool that allows for querying and exploring these spaces as well as a technique for visualizing thematic fit sub-spaces efficiently for web use.

• P16-4024     (0.35MB)
• https://www.researchgate.net/publication/306093691_Roleo_Visualising_Thematic_Fit_Spaces_on_the_Web

@inproceedings{sayeed-hong-demberg:2016:P16-4,
title = {Roleo: Visualising Thematic Fit Spaces on the Web},
author = {Asad Sayeed and Xudong Hong and Vera Demberg},
url = {https://www.researchgate.net/publication/306093691_Roleo_Visualising_Thematic_Fit_Spaces_on_the_Web},
year = {2016},
date = {2016-08-01},
booktitle = {Proceedings of ACL-2016 System Demonstrations},
pages = {139-144},
publisher = {Association for Computational Linguistics},
address = {Berlin, Germany},
abstract = {In this paper, we present Roleo, a web tool for visualizing the vector spaces generated by the evaluation of distributional memory (DM) models over thematic fit judgements. A thematic fit judgement is a rating of the selectional preference of a verb for an argument that fills a given thematic role. The DM approach to thematic fit judgements involves the construction of a sub-space in which a prototypical role-filler can be built for comparison to the noun being judged. We describe a publicly-accessible web tool that allows for querying and exploring these spaces as well as a technique for visualizing thematic fit sub-spaces efficiently for web use.},
pubstate = {published},
type = {inproceedings}
}

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LingoTurk is an open-source, freely available crowdsourcing client/server system aimed primarily at psycholinguistic experimentation where custom and specialized user interfaces are required but not supported by popular crowdsourcing task management platforms. LingoTurk enables user-friendly local hosting of experiments as well as condition management and participant exclusion. It is compatible with Amazon Mechanical Turk and Prolific Academic. New experiments can easily be set up via the Play Framework and the LingoTurk API, while multiple experiments can be managed from a single system.

• http://www.aclweb.org/anthology/N16-3012

@inproceedings{pusse-sayeed-demberg:2016:N16-3,
title = {LingoTurk: managing crowdsourced tasks for psycholinguistics},
author = {Florian Pusse and Asad Sayeed and Vera Demberg},
url = {http://www.aclweb.org/anthology/N16-3012},
year = {2016},
date = {2016-06-01},
booktitle = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations},
pages = {57-61},
publisher = {Association for Computational Linguistics},
address = {San Diego, California},
abstract = {LingoTurk is an open-source, freely available crowdsourcing client/server system aimed primarily at psycholinguistic experimentation where custom and specialized user interfaces are required but not supported by popular crowdsourcing task management platforms. LingoTurk enables user-friendly local hosting of experiments as well as condition management and participant exclusion. It is compatible with Amazon Mechanical Turk and Prolific Academic. New experiments can easily be set up via the Play Framework and the LingoTurk API, while multiple experiments can be managed from a single system.},
pubstate = {published},
type = {inproceedings}
}

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Most recent unsupervised methods in vector space semantics for assessing thematic fit (e.g. Erk, 2007; Baroni and Lenci, 2010; Sayeed and Demberg, 2014) create prototypical rolefillers without performing word sense disambiguation. This leads to a kind of sparsity problem: candidate role-fillers for different senses of the verb end up being measured by the same “yardstick”, the single prototypical role-filler.

In this work, we use three different feature spaces to construct robust unsupervised models of distributional semantics. We show that correlation with human judgements on thematic fit estimates can be improved consistently by clustering typical role-fillers and then calculating similarities of candidate rolefillers with these cluster centroids. The suggested methods can be used in any vector space model that constructs a prototype vector from a non-trivial set of typical vectors

• http://www.aclweb.org/anthology/N15-1003

@inproceedings{greenberg-sayeed-demberg:2015:NAACL-HLT,
title = {Improving Unsupervised Vector-Space Thematic Fit Evaluation via Role-Filler Prototype Clustering},
author = {Clayton Greenberg and Asad Sayeed and Vera Demberg},
url = {http://www.aclweb.org/anthology/N15-1003},
year = {2015},
date = {2015},
booktitle = {Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
pages = {21-31},
publisher = {Association for Computational Linguistics},
address = {Denver, Colorado},
abstract = {Most recent unsupervised methods in vector space semantics for assessing thematic fit (e.g. Erk, 2007; Baroni and Lenci, 2010; Sayeed and Demberg, 2014) create prototypical rolefillers without performing word sense disambiguation. This leads to a kind of sparsity problem: candidate role-fillers for different senses of the verb end up being measured by the same “yardstick”, the single prototypical role-filler. In this work, we use three different feature spaces to construct robust unsupervised models of distributional semantics. We show that correlation with human judgements on thematic fit estimates can be improved consistently by clustering typical role-fillers and then calculating similarities of candidate rolefillers with these cluster centroids. The suggested methods can be used in any vector space model that constructs a prototype vector from a non-trivial set of typical vectors},
pubstate = {published},
type = {inproceedings}
}

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• https://journals.openedition.org/ijcol/298

@conference{sayeed:demberg:shkadzko:2015:IJCOL,
title = {An Exploration of Semantic Features in an Unsupervised Thematic Fit Evaluation Framework},
author = {Asad Sayeed and Vera Demberg and Pavel Shkadzko},
url = {https://journals.openedition.org/ijcol/298},
year = {2015},
date = {2015},
booktitle = {IJCoL: Emerging Topics at the First Italian Conference on Computational Linguistics},
abstract = {

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Markers of negative polarity discourse relations, such as but, although and on the one hand… on the other hand have been shown to induce more processing difficulty than additive or causal markers (e.g., Murray, 1995), and to facilitate the processing of upcoming content (e.g., Köhne & Demberg, 2013). These markers have been argued to shape comprehenders‘ discourse expectations in a way that differs from what comprehenders would expect in the absence of such markers (Murray, 1995; Köhne & Demberg, 2013; Xiang & Kuperberg, 2014). Here, we present two studies on the nature of the expectations elicited by negative polarity connectives, addressing three primary questions: (i) How specific are the expectations elicited by ambiguous connectors such as but and although? (ii) Do the discourse expectations raised by a connective like on the one hand target any contrast or specifically on the other hand? (iii) Are expectations sensitive to discourse structure?

• https://detec2015.files.wordpress.com/2015/05/demberg.pdf

@inproceedings{demberg2015contrastive,
title = {Discourse Expectations Raised by Contrastive Connectives},
author = {Vera Demberg and Fatemeh Torabi Asr and Hannah Rohde},
url = {https://detec2015.files.wordpress.com/2015/05/demberg.pdf},
year = {2015},
date = {2015},
booktitle = {Conference on Discourse Expectations: Theoretical, Experimental, and Computational Perspectives (DETEC)},
abstract = {Markers of negative polarity discourse relations, such as but, although and on the one hand... on the other hand have been shown to induce more processing difficulty than additive or causal markers (e.g., Murray, 1995), and to facilitate the processing of upcoming content (e.g., K{\"o}hne & Demberg, 2013). These markers have been argued to shape comprehenders' discourse expectations in a way that differs from what comprehenders would expect in the absence of such markers (Murray, 1995; K{\"o}hne & Demberg, 2013; Xiang & Kuperberg, 2014). Here, we present two studies on the nature of the expectations elicited by negative polarity connectives, addressing three primary questions: (i) How specific are the expectations elicited by ambiguous connectors such as but and although? (ii) Do the discourse expectations raised by a connective like on the one hand target any contrast or specifically on the other hand? (iii) Are expectations sensitive to discourse structure?},
pubstate = {published},
type = {inproceedings}
}

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Many connectives, such as but and although, can be used to mark very similar sets of relations, see Table 1. Fraser 1999 proposes that each connective has a core meaning and that a more specific discourse relation will be inferred from the content of the involved clauses. This implies that connectives which can mark the same relations have the same core meaning, and that alternating between two such connectors should not change the meaning of the discourse. A fully distributional account (Asr & Demberg 2013), on the other hand, describes the information content of a connective based on its usage patterns. This means that a connective may even have different meanings in different sentence positions (i.e. when used sentenceinitially vs. between its arguments). This study shows how the fine-grained differences in the distribution of but vs. although vs. sentence-initial although affect text coherence. We created stories consisting of three sentences (see below) and normed them such that the first two sentences were equally acceptable in all conditions. The design was fully counter-balanced.

• CUNY2015_abstract     (0.12MB)
• https://www.coli.uni-saarland.de/~fatemeh/CUNY2015_abstract.pdf

@inproceedings{asr2015interpretation,
title = {A Discourse Connector's Distribution Determines Its Interpretation},
author = {Fatemeh Torabi Asr and Vera Demberg},
url = {https://www.coli.uni-saarland.de/~fatemeh/CUNY2015_abstract.pdf},
year = {2015},
date = {2015},
booktitle = {The 28th CUNY Conference on Human Sentence Processing 2015},
abstract = {Many connectives, such as but and although, can be used to mark very similar sets of relations, see Table 1. Fraser 1999 proposes that each connective has a core meaning and that a more specific discourse relation will be inferred from the content of the involved clauses. This implies that connectives which can mark the same relations have the same core meaning, and that alternating between two such connectors should not change the meaning of the discourse. A fully distributional account (Asr & Demberg 2013), on the other hand, describes the information content of a connective based on its usage patterns. This means that a connective may even have different meanings in different sentence positions (i.e. when used sentenceinitially vs. between its arguments). This study shows how the fine-grained differences in the distribution of but vs. although vs. sentence-initial although affect text coherence. We created stories consisting of three sentences (see below) and normed them such that the first two sentences were equally acceptable in all conditions. The design was fully counter-balanced.},
pubstate = {published},
type = {inproceedings}
}

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Discourse relations are the building blocks of a coherent text. The most important linguistic elements for constructing these relations are discourse markers. The presence of a discourse marker between two discourse segments provides information on the inferences that need to be made for interpretation of the two segments as a whole (e.g., because marks a reason).

This thesis presents a new framework for studying human communication at the level of discourse by adapting ideas from information theory. A discourse marker is viewed as a symbol with a measurable amount of relational information. This information is communicated by the writer of a text to guide the reader towards the right semantic decoding. To examine the information theoretic account of discourse markers, we conduct empirical corpus-based investigations, offline crowd-sourced studies and online laboratory experiments. The thesis contributes to computational linguistics by proposing a quantitative meaning representation for discourse markers and showing its advantages over the classic descriptive approaches. For the first time, we show that readers are very sensitive to the fine-grained information encoded in a discourse marker obtained from its natural usage and that writers use explicit marking for less expected relations in terms of linguistic and cognitive predictability. These findings open new directions for implementation of advanced natural language processing systems.

• https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/26688

@phdthesis{BentPhd05,
title = {An Information Theoretic Approach to Production and Comprehension of Discourse Markers},
author = {Fatemeh Torabi Asr},
url = {https://publikationen.sulb.uni-saarland.de/handle/20.500.11880/26688},
year = {2015},
date = {2015},
school = {Saarland University},
address = {Saarbruecken, Germany},
abstract = {Discourse relations are the building blocks of a coherent text. The most important linguistic elements for constructing these relations are discourse markers. The presence of a discourse marker between two discourse segments provides information on the inferences that need to be made for interpretation of the two segments as a whole (e.g., because marks a reason). This thesis presents a new framework for studying human communication at the level of discourse by adapting ideas from information theory. A discourse marker is viewed as a symbol with a measurable amount of relational information. This information is communicated by the writer of a text to guide the reader towards the right semantic decoding. To examine the information theoretic account of discourse markers, we conduct empirical corpus-based investigations, offline crowd-sourced studies and online laboratory experiments. The thesis contributes to computational linguistics by proposing a quantitative meaning representation for discourse markers and showing its advantages over the classic descriptive approaches. For the first time, we show that readers are very sensitive to the fine-grained information encoded in a discourse marker obtained from its natural usage and that writers use explicit marking for less expected relations in terms of linguistic and cognitive predictability. These findings open new directions for implementation of advanced natural language processing systems.},
pubstate = {published},
type = {phdthesis}
}

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• vst     (0.09MB)
• https://ojs.ub.uni-konstanz.de/sub/index.php/sub/article/view/284

@inproceedings{SuB2015,
title = {Representing the Effort in Resolving Ambiguous Scope},
author = {Asad Sayeed},
url = {https://ojs.ub.uni-konstanz.de/sub/index.php/sub/article/view/284},
year = {2015},
date = {2015},
booktitle = {Sinn und Bedeutung 20},
address = {T{\"u}bingen, Germany},
abstract = {

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@inproceedings{asr2015distributionalApproach,
title = {A Distributional Account of Discourse Connectives and its Effect on Fine-grained Inferences},
author = {Fatemeh Torabi Asr and Vera Demberg},
year = {2015},
date = {2015},
booktitle = {Text-link Conference},
address = {Louvain, Belgium},
pubstate = {published},
type = {inproceedings}
}

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About half of the discourse relations annotated in Penn Discourse Treebank (Prasad et al., 2008) are not explicitly marked using a discourse connective. But we do not have extensive theories of when or why a discourse relation is marked explicitly or when the connective is omitted. Asr and Demberg (2012a) have suggested an information-theoretic perspective according to which discourse connectives are more likely to be omitted when they are marking a relation that is expected or predictable. This account is based on the Uniform Information Density theory (Levy and Jaeger, 2007), which suggests that speakers choose among alternative formulations that are allowed in their language the ones that achieve a roughly uniform rate of information transmission. Optional discourse markers should thus be omitted if they would lead to a trough in information density, and be inserted in order to avoid peaks in information density. We here test this hypothesis by observing how far a specific cue, negation in any form, affects the discourse relations that can be predicted to hold in a text, and how the presence of this cue in turn affects the use of explicit discourse connectives.

• https://www.semanticscholar.org/paper/Uniform-Information-Density-at-the-Level-of-Markers-Asr-Demberg/cee6437e3aba3e772ef8cc7e9aaf3d7ba1114d8b

@inproceedings{asr2015uniform,
title = {Uniform Information Density at the Level of Discourse Relations: Negation Markers and Discourse Connective Omission},
author = {Fatemeh Torabi Asr and Vera Demberg},
url = {https://www.semanticscholar.org/paper/Uniform-Information-Density-at-the-Level-of-Markers-Asr-Demberg/cee6437e3aba3e772ef8cc7e9aaf3d7ba1114d8b},
year = {2015},
date = {2015},
booktitle = {IWCS 2015},
pages = {118},
abstract = {About half of the discourse relations annotated in Penn Discourse Treebank (Prasad et al., 2008) are not explicitly marked using a discourse connective. But we do not have extensive theories of when or why a discourse relation is marked explicitly or when the connective is omitted. Asr and Demberg (2012a) have suggested an information-theoretic perspective according to which discourse connectives are more likely to be omitted when they are marking a relation that is expected or predictable. This account is based on the Uniform Information Density theory (Levy and Jaeger, 2007), which suggests that speakers choose among alternative formulations that are allowed in their language the ones that achieve a roughly uniform rate of information transmission. Optional discourse markers should thus be omitted if they would lead to a trough in information density, and be inserted in order to avoid peaks in information density. We here test this hypothesis by observing how far a specific cue, negation in any form, affects the discourse relations that can be predicted to hold in a text, and how the presence of this cue in turn affects the use of explicit discourse connectives.},
pubstate = {published},
type = {inproceedings}
}

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• https://www.bibsonomy.org/bibtex/ddebcecc8adb8f40a0abf87294b11a02

@inproceedings{AMLaP2015a,
title = {To What Extent Do We Adapt Spoken Word Durations to a Domain?},
author = {Asad Sayeed and Stefan Fischer and Vera Demberg},
url = {https://www.bibsonomy.org/bibtex/ddebcecc8adb8f40a0abf87294b11a02},
year = {2015},
date = {2015},
booktitle = {Architectures and mechanisms for language processing (AMLaP)},
address = {Malta},
pubstate = {published},
type = {inproceedings}
}

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While several data sets for evaluating thematic fit of verb-role-filler triples exist, they do not control for verb polysemy. Thus, it is unclear how verb polysemy affects human ratings of thematic fit and how best to model that. We present a new dataset of human ratings on high vs. low-polysemy verbs matched for verb frequency, together with high vs. low-frequency and well-fitting vs. poorly-fitting patient rolefillers. Our analyses show that low-polysemy verbs produce stronger thematic fit judgements than verbs with higher polysemy. Rolefiller frequency, on the other hand, had little effect on ratings. We show that these results can best be modeled in a vector space using a clustering technique to create multiple prototype vectors representing different “senses” of the verb.

• http://www.aclweb.org/anthology/W15-1106

@inproceedings{greenberg-demberg-sayeed:2015:CMCL,
title = {Verb Polysemy and Frequency Effects in Thematic Fit Modeling},
author = {Clayton Greenberg and Vera Demberg and Asad Sayeed},
url = {http://www.aclweb.org/anthology/W15-1106},
year = {2015},
date = {2015-06-01},
booktitle = {Proceedings of the 6th Workshop on Cognitive Modeling and Computational Linguistics},
pages = {48-57},
publisher = {Association for Computational Linguistics},
address = {Denver, Colorado},
abstract = {While several data sets for evaluating thematic fit of verb-role-filler triples exist, they do not control for verb polysemy. Thus, it is unclear how verb polysemy affects human ratings of thematic fit and how best to model that. We present a new dataset of human ratings on high vs. low-polysemy verbs matched for verb frequency, together with high vs. low-frequency and well-fitting vs. poorly-fitting patient rolefillers. Our analyses show that low-polysemy verbs produce stronger thematic fit judgements than verbs with higher polysemy. Rolefiller frequency, on the other hand, had little effect on ratings. We show that these results can best be modeled in a vector space using a clustering technique to create multiple prototype vectors representing different “senses” of the verb.},
pubstate = {published},
type = {inproceedings}
}

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