Bonnie Webber

Also published as: B.L. Nash-Webber, B. Webber, Bonnie Lynn Webber, Bonnie L. Webber


2020

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Shallow Discourse Annotation for Chinese TED Talks
Wanqiu Long | Xinyi Cai | James Reid | Bonnie Webber | Deyi Xiong
Proceedings of the 12th Language Resources and Evaluation Conference

Text corpora annotated with language-related properties are an important resource for the development of Language Technology. The current work contributes a new resource for Chinese Language Technology and for Chinese-English translation, in the form of a set of TED talks (some originally given in English, some in Chinese) that have been annotated with discourse relations in the style of the Penn Discourse TreeBank, adapted to properties of Chinese text that are not present in English. The resource is currently unique in annotating discourse-level properties of planned spoken monologues rather than of written text. An inter-annotator agreement study demonstrates that the annotation scheme is able to achieve highly reliable results.

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Reducing Quantity Hallucinations in Abstractive Summarization
Zheng Zhao | Shay B. Cohen | Bonnie Webber
Findings of the Association for Computational Linguistics: EMNLP 2020

It is well-known that abstractive summaries are subject to hallucination—including material that is not supported by the original text. While summaries can be made hallucination-free by limiting them to general phrases, such summaries would fail to be very informative. Alternatively, one can try to avoid hallucinations by verifying that any specific entities in the summary appear in the original text in a similar context. This is the approach taken by our system, Herman. The system learns to recognize and verify quantity entities (dates, numbers, sums of money, etc.) in a beam-worth of abstractive summaries produced by state-of-the-art models, in order to up-rank those summaries whose quantity terms are supported by the original text. Experimental results demonstrate that the ROUGE scores of such up-ranked summaries have a higher Precision than summaries that have not been up-ranked, without a comparable loss in Recall, resulting in higher F1. Preliminary human evaluation of up-ranked vs. original summaries shows people’s preference for the former.

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Extending Implicit Discourse Relation Recognition to the PDTB-3
Li Liang | Zheng Zhao | Bonnie Webber
Proceedings of the First Workshop on Computational Approaches to Discourse

The PDTB-3 contains many more Implicit discourse relations than the previous PDTB-2. This is in part because implicit relations have now been annotated within sentences as well as between them. In addition, some now co-occur with explicit discourse relations, instead of standing on their own. Here we show that while this can complicate the problem of identifying the location of implicit discourse relations, it can in turn simplify the problem of identifying their senses. We present data to support this claim, as well as methods that can serve as a non-trivial baseline for future state-of-the-art recognizers for implicit discourse relations.

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Querent Intent in Multi-Sentence Questions
Laurie Burchell | Jie Chi | Tom Hosking | Nina Markl | Bonnie Webber
Proceedings of the 14th Linguistic Annotation Workshop

Multi-sentence questions (MSQs) are sequences of questions connected by relations which, unlike sequences of standalone questions, need to be answered as a unit. Following Rhetorical Structure Theory (RST), we recognise that different “question discourse relations” between the subparts of MSQs reflect different speaker intents, and consequently elicit different answering strategies. Correctly identifying these relations is therefore a crucial step in automatically answering MSQs. We identify five different types of MSQs in English, and define five novel relations to describe them. We extract over 162,000 MSQs from Stack Exchange to enable future research. Finally, we implement a high-precision baseline classifier based on surface features.

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Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Bonnie Webber | Trevor Cohn | Yulan He | Yang Liu
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

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TED-CDB: A Large-Scale Chinese Discourse Relation Dataset on TED Talks
Wanqiu Long | Bonnie Webber | Deyi Xiong
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

As different genres are known to differ in their communicative properties and as previously, for Chinese, discourse relations have only been annotated over news text, we have created the TED-CDB dataset. TED-CDB comprises a large set of TED talks in Chinese that have been manually annotated according to the goals and principles of Penn Discourse Treebank, but adapted to features that are not present in English. It serves as a unique Chinese corpus of spoken discourse. Benchmark experiments show that TED-CDB poses a challenge for state-of-the-art discourse relation classifiers, whose F1 performance on 4-way classification is 60%. This is a dramatic drop of 35% from performance on the news text in the Chinese Discourse Treebank. Transfer learning experiments have been carried out with the TED-CDB for both same-language cross-domain transfer and same-domain cross-language transfer. Both demonstrate that the TED-CDB can improve the performance of systems being developed for languages other than Chinese and would be helpful for insufficient or unbalanced data in other corpora. The dataset and our Chinese annotation guidelines will be made freely available.

2019

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GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue
Jun Quan | Deyi Xiong | Bonnie Webber | Changjian Hu
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Ellipsis and co-reference are common and ubiquitous especially in multi-turn dialogues. In this paper, we treat the resolution of ellipsis and co-reference in dialogue as a problem of generating omitted or referred expressions from the dialogue context. We therefore propose a unified end-to-end Generative Ellipsis and CO-reference Resolution model (GECOR) in the context of dialogue. The model can generate a new pragmatically complete user utterance by alternating the generation and copy mode for each user utterance. A multi-task learning framework is further proposed to integrate the GECOR into an end-to-end task-oriented dialogue. In order to train both the GECOR and the multi-task learning framework, we manually construct a new dataset on the basis of the public dataset CamRest676 with both ellipsis and co-reference annotation. On this dataset, intrinsic evaluations on the resolution of ellipsis and co-reference show that the GECOR model significantly outperforms the sequence-to-sequence (seq2seq) baseline model in terms of EM, BLEU and F1 while extrinsic evaluations on the downstream dialogue task demonstrate that our multi-task learning framework with GECOR achieves a higher success rate of task completion than TSCP, a state-of-the-art end-to-end task-oriented dialogue model.

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Ambiguity in Explicit Discourse Connectives
Bonnie Webber | Rashmi Prasad | Alan Lee
Proceedings of the 13th International Conference on Computational Semantics - Long Papers

Discourse connectives are known to be subject to both usage and sense ambiguity, as has already been discussed in the literature. But discourse connectives are no different from other linguistic expressions in being subject to other types of ambiguity as well. Four are illustrated and discussed here.

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A Framework for Annotating ‘Related Works’ to Support Feedback to Novice Writers
Arlene Casey | Bonnie Webber | Dorota Glowacka
Proceedings of the 13th Linguistic Annotation Workshop

Understanding what is expected of academic writing can be difficult for novice writers to assimilate, and recent years have seen several automated tools become available to support academic writing. Our work presents a framework for annotating features of the Related Work section of academic writing, that supports writer feedback.

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Classifying Author Intention for Writer Feedback in Related Work
Arlene Casey | Bonnie Webber | Dorota Glowacka
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)

The ability to produce high-quality publishable material is critical to academic success but many Post-Graduate students struggle to learn to do so. While recent years have seen an increase in tools designed to provide feedback on aspects of writing, one aspect that has so far been neglected is the Related Work section of academic research papers. To address this, we have trained a supervised classifier on a corpus of 94 Related Work sections and evaluated it against a manually annotated gold standard. The classifier uses novel features pertaining to citation types and co-reference, along with patterns found from studying Related Works. We show that these novel features contribute to classifier performance with performance being favourable compared to other similar works that classify author intentions and consider feedback for academic writing.

2018

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Evaluating Machine Translation Performance on Chinese Idioms with a Blacklist Method
Yutong Shao | Rico Sennrich | Bonnie Webber | Federico Fancellu
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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NegPar: A parallel corpus annotated for negation
Qianchu Liu | Federico Fancellu | Bonnie Webber
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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Getting to “Hearer-old”: Charting Referring Expressions Across Time
Ieva Staliūnaitė | Hannah Rohde | Bonnie Webber | Annie Louis
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

When a reader is first introduced to an entity, its referring expression must describe the entity. For entities that are widely known, a single word or phrase often suffices. This paper presents the first study of how expressions that refer to the same entity develop over time. We track thousands of person and organization entities over 20 years of New York Times (NYT). As entities move from hearer-new (first introduction to the NYT audience) to hearer-old (common knowledge) status, we show empirically that the referring expressions along this trajectory depend on the type of the entity, and exhibit linguistic properties related to becoming common knowledge (e.g., shorter length, less use of appositives, more definiteness). These properties can also be used to build a model to predict how long it will take for an entity to reach hearer-old status. Our results reach 10-30% absolute improvement over a majority-class baseline.

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Discourse Coherence: Concurrent Explicit and Implicit Relations
Hannah Rohde | Alexander Johnson | Nathan Schneider | Bonnie Webber
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Theories of discourse coherence posit relations between discourse segments as a key feature of coherent text. Our prior work suggests that multiple discourse relations can be simultaneously operative between two segments for reasons not predicted by the literature. Here we test how this joint presence can lead participants to endorse seemingly divergent conjunctions (e.g., BUT and SO) to express the link they see between two segments. These apparent divergences are not symptomatic of participant naivety or bias, but arise reliably from the concurrent availability of multiple relations between segments – some available through explicit signals and some via inference. We believe that these new results can both inform future progress in theoretical work on discourse coherence and lead to higher levels of performance in discourse parsing.

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Obituary: Aravind K. Joshi
Bonnie Webber
Computational Linguistics, Volume 44, Issue 3 - September 2018

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Discourse Annotation in the PDTB: The Next Generation
Rashmi Prasad | Bonnie Webber | Alan Lee
Proceedings 14th Joint ACL - ISO Workshop on Interoperable Semantic Annotation

2017

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Detecting negation scope is easy, except when it isn’t
Federico Fancellu | Adam Lopez | Bonnie Webber | Hangfeng He
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

Several corpora have been annotated with negation scope—the set of words whose meaning is negated by a cue like the word “not”—leading to the development of classifiers that detect negation scope with high accuracy. We show that for nearly all of these corpora, this high accuracy can be attributed to a single fact: they frequently annotate negation scope as a single span of text delimited by punctuation. For negation scopes not of this form, detection accuracy is low and under-sampling the easy training examples does not substantially improve accuracy. We demonstrate that this is partly an artifact of annotation guidelines, and we argue that future negation scope annotation efforts should focus on these more difficult cases.

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Discourse Relations and Conjoined VPs: Automated Sense Recognition
Valentina Pyatkin | Bonnie Webber
Proceedings of the Student Research Workshop at the 15th Conference of the European Chapter of the Association for Computational Linguistics

Sense classification of discourse relations is a sub-task of shallow discourse parsing. Discourse relations can occur both across sentences (inter-sentential) and within sentences (intra-sentential), and more than one discourse relation can hold between the same units. Using a newly available corpus of discourse-annotated intra-sentential conjoined verb phrases, we demonstrate a sequential classification pipeline for their multi-label sense classification. We assess the importance of each feature used in the classification, the feature scope, and what is lost in moving from gold standard manual parses to the output of an off-the-shelf parser.

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Universal Dependencies to Logical Form with Negation Scope
Federico Fancellu | Siva Reddy | Adam Lopez | Bonnie Webber
Proceedings of the Workshop Computational Semantics Beyond Events and Roles

Many language technology applications would benefit from the ability to represent negation and its scope on top of widely-used linguistic resources. In this paper, we investigate the possibility of obtaining a first-order logic representation with negation scope marked using Universal Dependencies. To do so, we enhance UDepLambda, a framework that converts dependency graphs to logical forms. The resulting UDepLambda¬ is able to handle phenomena related to scope by means of an higher-order type theory, relevant not only to negation but also to universal quantification and other complex semantic phenomena. The initial conversion we did for English is promising, in that one can represent the scope of negation also in the presence of more complex phenomena such as universal quantifiers.

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Neural Networks for Negation Cue Detection in Chinese
Hangfeng He | Federico Fancellu | Bonnie Webber
Proceedings of the Workshop Computational Semantics Beyond Events and Roles

Negation cue detection involves identifying the span inherently expressing negation in a negative sentence. In Chinese, negative cue detection is complicated by morphological proprieties of the language. Previous work has shown that negative cue detection in Chinese can benefit from specific lexical and morphemic features, as well as cross-lingual information. We show here that they are not necessary: A bi-directional LSTM can perform equally well, with minimal feature engineering. In particular, the use of a character-based model allows us to capture characteristics of negation cues in Chinese using word-embedding information only. Not only does our model performs on par with previous work, further error analysis clarifies what problems remain to be addressed.

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Proceedings of the Third Workshop on Discourse in Machine Translation
Bonnie Webber | Andrei Popescu-Belis | Jörg Tiedemann
Proceedings of the Third Workshop on Discourse in Machine Translation

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Exploring Substitutability through Discourse Adverbials and Multiple Judgments
Hannah Rohde | Anna Dickinson | Nathan Schneider | Annie Louis | Bonnie Webber
IWCS 2017 - 12th International Conference on Computational Semantics - Long papers

2016

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Inconsistency Detection in Semantic Annotation
Nora Hollenstein | Nathan Schneider | Bonnie Webber
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Inconsistencies are part of any manually annotated corpus. Automatically finding these inconsistencies and correcting them (even manually) can increase the quality of the data. Past research has focused mainly on detecting inconsistency in syntactic annotation. This work explores new approaches to detecting inconsistency in semantic annotation. Two ranking methods are presented in this paper: a discrepancy ranking and an entropy ranking. Those methods are then tested and evaluated on multiple corpora annotated with multiword expressions and supersense labels. The results show considerable improvements in detecting inconsistency candidates over a random baseline. Possible applications of methods for inconsistency detection are improving the annotation procedure as well as the guidelines and correcting errors in completed annotations.

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CoNLL 2016 Shared Task on Multilingual Shallow Discourse Parsing
Nianwen Xue | Hwee Tou Ng | Sameer Pradhan | Attapol Rutherford | Bonnie Webber | Chuan Wang | Hongmin Wang
Proceedings of the CoNLL-16 shared task

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Annotating Discourse Relations with the PDTB Annotator
Alan Lee | Rashmi Prasad | Bonnie Webber | Aravind K. Joshi
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: System Demonstrations

The PDTB Annotator is a tool for annotating and adjudicating discourse relations based on the annotation framework of the Penn Discourse TreeBank (PDTB). This demo describes the benefits of using the PDTB Annotator, gives an overview of the PDTB Framework and discusses the tool’s features, setup requirements and how it can also be used for adjudication.

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Neural Networks For Negation Scope Detection
Federico Fancellu | Adam Lopez | Bonnie Webber
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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A Discourse-Annotated Corpus of Conjoined VPs
Bonnie Webber | Rashmi Prasad | Alan Lee | Aravind Joshi
Proceedings of the 10th Linguistic Annotation Workshop held in conjunction with ACL 2016 (LAW-X 2016)

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Filling in the Blanks in Understanding Discourse Adverbials: Consistency, Conflict, and Context-Dependence in a Crowdsourced Elicitation Task
Hannah Rohde | Anna Dickinson | Nathan Schneider | Christopher N. L. Clark | Annie Louis | Bonnie Webber
Proceedings of the 10th Linguistic Annotation Workshop held in conjunction with ACL 2016 (LAW-X 2016)

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Findings of the 2016 WMT Shared Task on Cross-lingual Pronoun Prediction
Liane Guillou | Christian Hardmeier | Preslav Nakov | Sara Stymne | Jörg Tiedemann | Yannick Versley | Mauro Cettolo | Bonnie Webber | Andrei Popescu-Belis
Proceedings of the First Conference on Machine Translation: Volume 2, Shared Task Papers

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Proceedings of the Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods
Annie Louis | Michael Roth | Bonnie Webber | Michael White | Luke Zettlemoyer
Proceedings of the Workshop on Uphill Battles in Language Processing: Scaling Early Achievements to Robust Methods

2015

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Translating Negation: Induction, Search And Model Errors
Federico Fancellu | Bonnie Webber
Proceedings of the Ninth Workshop on Syntax, Semantics and Structure in Statistical Translation

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Translating Negation: A Manual Error Analysis
Federico Fancellu | Bonnie Webber
Proceedings of the Second Workshop on Extra-Propositional Aspects of Meaning in Computational Semantics (ExProM 2015)

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Proceedings of the Second Workshop on Discourse in Machine Translation
Bonnie Webber | Marine Carpuat | Andrei Popescu-Belis | Christian Hardmeier
Proceedings of the Second Workshop on Discourse in Machine Translation

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Analysing ParCor and its Translations by State-of-the-art SMT Systems
Liane Guillou | Bonnie Webber
Proceedings of the Second Workshop on Discourse in Machine Translation

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A Maximum Entropy Classifier for Cross-Lingual Pronoun Prediction
Dominikus Wetzel | Adam Lopez | Bonnie Webber
Proceedings of the Second Workshop on Discourse in Machine Translation

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Proceedings of the First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics
Michael Roth | Annie Louis | Bonnie Webber | Tim Baldwin
Proceedings of the First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics

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Recovering discourse relations: Varying influence of discourse adverbials
Hannah Rohde | Anna Dickinson | Chris Clark | Annie Louis | Bonnie Webber
Proceedings of the First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics

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Bridging Sentential and Discourse-level Semantics through Clausal Adjuncts
Rashmi Prasad | Bonnie Webber | Alan Lee | Sameer Pradhan | Aravind Joshi
Proceedings of the First Workshop on Linking Computational Models of Lexical, Sentential and Discourse-level Semantics

2014

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Reflections on the Penn Discourse TreeBank, Comparable Corpora, and Complementary Annotation
Rashmi Prasad | Bonnie Webber | Aravind Joshi
Computational Linguistics, Volume 40, Issue 4 - December 2014

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Structured and Unstructured Cache Models for SMT Domain Adaptation
Annie Louis | Bonnie Webber
Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics

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Applying the semantics of negation to SMT through n-best list re-ranking
Federico Fancellu | Bonnie Webber
Proceedings of the 14th Conference of the European Chapter of the Association for Computational Linguistics

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Discourse for Machine Translation.
Bonnie Webber
Proceedings of the 28th Pacific Asia Conference on Language, Information and Computing

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ParCor 1.0: A Parallel Pronoun-Coreference Corpus to Support Statistical MT
Liane Guillou | Christian Hardmeier | Aaron Smith | Jörg Tiedemann | Bonnie Webber
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We present ParCor, a parallel corpus of texts in which pronoun coreference ― reduced coreference in which pronouns are used as referring expressions ― has been annotated. The corpus is intended to be used both as a resource from which to learn systematic differences in pronoun use between languages and ultimately for developing and testing informed Statistical Machine Translation systems aimed at addressing the problem of pronoun coreference in translation. At present, the corpus consists of a collection of parallel English-German documents from two different text genres: TED Talks (transcribed planned speech), and EU Bookshop publications (written text). All documents in the corpus have been manually annotated with respect to the type and location of each pronoun and, where relevant, its antecedent. We provide details of the texts that we selected, the guidelines and tools used to support annotation and some corpus statistics. The texts in the corpus have already been translated into many languages, and we plan to expand the corpus into these other languages, as well as other genres, in the future.

2013

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What excludes an Alternative in Coherence Relations?
Bonnie Webber
Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers

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Proceedings of the Workshop on Discourse in Machine Translation
Bonnie Webber | Andrei Popescu-Belis | Katja Markert | Jörg Tiedemann
Proceedings of the Workshop on Discourse in Machine Translation

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Implicitation of Discourse Connectives in (Machine) Translation
Thomas Meyer | Bonnie Webber
Proceedings of the Workshop on Discourse in Machine Translation

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Discourse Relations, Discourse Structure, Discourse Semantics
Bonnie Webber
Proceedings of the SIGDIAL 2013 Conference

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Evaluating a City Exploration Dialogue System with Integrated Question-Answering and Pedestrian Navigation
Srinivasan Janarthanam | Oliver Lemon | Phil Bartie | Tiphaine Dalmas | Anna Dickinson | Xingkun Liu | William Mackaness | Bonnie Webber
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Concurrent Discourse Relations
Bonnie Webber
Proceedings of the Australasian Language Technology Association Workshop 2013 (ALTA 2013)

2012

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Book Review: Discourse Processing by Manfred Stede
Bonnie Webber
Computational Linguistics, Volume 38, Issue 4 - December 2012

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BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Kevin B. Cohen | Dina Demner-Fushman | Sophia Ananiadou | Bonnie Webber | Jun’ichi Tsujii | John Pestian
BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing

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Discourse Structure and Computation: Past, Present and Future
Bonnie Webber | Aravind Joshi
Proceedings of the ACL-2012 Special Workshop on Rediscovering 50 Years of Discoveries

2011

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Proceedings of BioNLP 2011 Workshop
Kevin Bretonnel Cohen | Dina Demner-Fushman | Sophia Ananiadou | John Pestian | Jun’ichi Tsujii | Bonnie Webber
Proceedings of BioNLP 2011 Workshop

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Invited Paper: Discourse Structures and Language Technologies
Bonnie Webber
Proceedings of the 18th Nordic Conference of Computational Linguistics (NODALIDA 2011)

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Squibs: Stable Classification of Text Genres
Philipp Petrenz | Bonnie Webber
Computational Linguistics, Volume 37, Issue 2 - June 2011

2010

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Proceedings of the 2010 Workshop on Biomedical Natural Language Processing
K. Bretonnel Cohen | Dina Demner-Fushman | Sophia Ananiadou | John Pestian | Jun’ichi Tsujii | Bonnie Webber
Proceedings of the 2010 Workshop on Biomedical Natural Language Processing

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Realization of Discourse Relations by Other Means: Alternative Lexicalizations
Rashmi Prasad | Aravind Joshi | Bonnie Webber
Coling 2010: Posters

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Discourse Structure: Theory, Practice and Use
Bonnie Webber | Markus Egg | Valia Kordoni
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts

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Exploiting Scope for Shallow Discourse Parsing
Rashmi Prasad | Aravind Joshi | Bonnie Webber
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present an approach to automatically identifying the arguments of discourse connectives based on data from the Penn Discourse Treebank. Of the two arguments of connectives, called Arg1 and Arg2, we focus on Arg1, which has proven more challenging to identify. Our approach employs a sentence-based representation of arguments, and distinguishes ""intra-sentential connectives"", which take both their arguments in the same sentence, from ""inter-sentential connectives"", whose arguments are found in different sentences. The latter are further distinguished by paragraph position into ""ParaInit"" connectives, which appear in a paragraph-initial sentence, and ""ParaNonInit"" connectives, which appear elsewhere. The paper focusses on predicting Arg1 of Inter-sentential ParaNonInit connectives, presenting a set of scope-based filters that reduce the search space for Arg1 from all the previous sentences in the paragraph to a subset of them. For cases where these filters do not uniquely identify Arg1, coreference-based heuristics are employed. Our analysis shows an absolute 3% performance improvement over the high baseline of 83.3% for identifying Arg1 of Inter-sentential ParaNonInit connectives.

2009

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Proceedings of the BioNLP 2009 Workshop
K. Bretonnel Cohen | Dina Demner-Fushman | Sophia Ananiadou | John Pestian | Jun’ichi Tsujii | Bonnie Webber
Proceedings of the BioNLP 2009 Workshop

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Genre distinctions for discourse in the Penn TreeBank
Bonnie Webber
Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP

2008

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The Penn Discourse TreeBank 2.0.
Rashmi Prasad | Nikhil Dinesh | Alan Lee | Eleni Miltsakaki | Livio Robaldo | Aravind Joshi | Bonnie Webber
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

We present the second version of the Penn Discourse Treebank, PDTB-2.0, describing its lexically-grounded annotations of discourse relations and their two abstract object arguments over the 1 million word Wall Street Journal corpus. We describe all aspects of the annotation, including (a) the argument structure of discourse relations, (b) the sense annotation of the relations, and (c) the attribution of discourse relations and each of their arguments. We list the differences between PDTB-1.0 and PDTB-2.0. We present representative statistics for several aspects of the annotation in the corpus.

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A Discourse Resource for Turkish: Annotating Discourse Connectives in the METU Corpus
Deniz Zeyrek | Bonnie Webber
Proceedings of the 6th Workshop on Asian Language Resources

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Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Dina Demner-Fushman | Sophia Ananiadou | Kevin Bretonnel Cohen | John Pestian | Jun’ichi Tsujii | Bonnie Webber
Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing

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Topic Indexing and Retrieval for Factoid QA
Kisuh Ahn | Bonnie Webber
Coling 2008: Proceedings of the 2nd workshop on Information Retrieval for Question Answering

2007

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Marking time in developmental biology
Gail Sinclair | Bonnie Webber
Biological, translational, and clinical language processing

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Question Answering based on Semantic Roles
Michael Kaisser | Bonnie Webber
ACL 2007 Workshop on Deep Linguistic Processing

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Discourse Annotation Working Group Report
Manfred Stede | Janyce Wiebe | Eva Hajičová | Brian Reese | Simone Teufel | Bonnie Webber | Theresa Wilson
Proceedings of the Linguistic Annotation Workshop

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Last Words: Breaking News: Changing Attitudes and Practices
Bonnie Webber
Computational Linguistics, Volume 33, Number 4, December 2007

2006

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Annotating Attribution in the Penn Discourse TreeBank
Rashmi Prasad | Nikhil Dinesh | Alan Lee | Aravind Joshi | Bonnie Webber
Proceedings of the Workshop on Sentiment and Subjectivity in Text

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Marking Time in Developmental Biology: Annotating Developmental Events and their Links with Molecular Events
Gail Sinclair | Bonnie Webber | Duncan Davidson
Proceedings of the Workshop on Annotating and Reasoning about Time and Events

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Extracting formal specifications from natural language regulatory documents
Nikhil Dinesh | Aravind Joshi | Insup Lee | Bonnie Webber
Proceedings of the Fifth International Workshop on Inference in Computational Semantics (ICoS-5)

2005

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Attribution and the (Non-)Alignment of Syntactic and Discourse Arguments of Connectives
Nikhil Dinesh | Alan Lee | Eleni Miltsakaki | Rashmi Prasad | Aravind Joshi | Bonnie Webber
Proceedings of the Workshop on Frontiers in Corpus Annotations II: Pie in the Sky

2004

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The Penn Discourse Treebank
Eleni Miltsakaki | Rashmi Prasad | Aravind Joshi | Bonnie Webber
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

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Annotation and Data Mining of the Penn Discourse TreeBank
Rashmi Prasad | Eleni Miltsakaki | Aravind Joshi | Bonnie Webber
Proceedings of the Workshop on Discourse Annotation

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Classification from Full Text: A Comparison of Canonical Sections of Scientific Papers
Gail Sinclair | Bonnie Webber
Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications (NLPBA/BioNLP)

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Annotating Discourse Connectives and Their Arguments
Eleni Miltsakaki | Aravind Joshi | Rashmi Prasad | Bonnie Webber
Proceedings of the Workshop Frontiers in Corpus Annotation at HLT-NAACL 2004

2003

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Grounding spatial named entities for information extraction and question answering
Jochen L. Leidner | Gail Sinclair | Bonnie Webber
Proceedings of the HLT-NAACL 2003 Workshop on Analysis of Geographic References

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Automatic Multi-Layer Corpus Annotation for Evaluation Question Answering Methods: CBC4Kids
Jochen L. Leidner | Tiphaine Dalmas | Bonnie Webber | Johan Bos | Claire Grover
Proceedings of 4th International Workshop on Linguistically Interpreted Corpora (LINC-03) at EACL 2003

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Anaphoric arguments of discourse connectives: Semantic properties of antecedents versus non-antecedents
Eleni Miltsakaki | Cassandre Creswell | Katherine Forbes | Aravind Joshi | Bonnie Webber
Proceedings of the 2003 EACL Workshop on The Computational Treatment of Anaphora

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Anaphora and Discourse Structure
Bonnie Webber | Matthew Stone | Aravind Joshi | Alistair Knott
Computational Linguistics, Volume 29, Number 4, December 2003

2002

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A Semantic Account of Adverbials as Discourse Connectives
Kate Forbes | Bonnie Webber
Proceedings of the Third SIGdial Workshop on Discourse and Dialogue

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Enhanced natural language access to anatomically-indexed data
Gail Sinclair | Bonnie Webber | Duncan Davidson
Proceedings of the ACL-02 Workshop on Natural Language Processing in the Biomedical Domain

1999

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Discourse Relations: A Structural and Presuppositional Account Using Lexicalised TAG
Bonnie Webber | Alistair Knott | Matthew Stone | Aravind Joshi
Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics

1998

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Describing discourse semantics
Claire Gardent | Bonnie Webber
Proceedings of the Fourth International Workshop on Tree Adjoining Grammars and Related Frameworks (TAG+4)

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Anchoring a Lexicalized Tree-Adjoining Grammar for Discourse
Bonnie Lynn Webber | Aravind K. Joshi
Discourse Relations and Discourse Markers

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Textual Economy Through Close Coupling of Syntax and Semantics
Matthew Stone | Bonnie Webber
Natural Language Generation

1997

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Expectations in Incremental Discourse Processing
Dan Cristea | Bonnie Webber
35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics

1994

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Research in Natural Language Processing
A. Joshi | M. Marcus | M. Steedman | B. Webber
Human Language Technology: Proceedings of a Workshop held at Plainsboro, New Jersey, March 8-11, 1994

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Upholding the Maxim of Relevance during Patient-Centered Activities
Abigail S. Gertner | Bonnie L. Webber | John R. Clarke
Fourth Conference on Applied Natural Language Processing

1993

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Natural Language Research
Aravind Joshi | Mitch Marcus | Mark Steedman | Bonnie Webber
Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993

1992

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Natural Language Research
Aravind Joshi | Mitch Marcus | Mark Steedman | Bonnie Webber
Speech and Natural Language: Proceedings of a Workshop Held at Harriman, New York, February 23-26, 1992

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Accommodating Context Change
Bonnie Lynn Webber | Breck Baldwin
30th Annual Meeting of the Association for Computational Linguistics

1991

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Natural Language Research
Aravind K. Joshi | Mitch Marcus | Mark Steedman | Bonnie Webber
Speech and Natural Language: Proceedings of a Workshop Held at Pacific Grove, California, February 19-22, 1991

1990

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Free Adjuncts in Natural Language Instructions
Bonnie Lynn Webber | Barbara Di Eugenio
COLING 1990 Volume 2: Papers presented to the 13th International Conference on Computational Linguistics

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Natural Language Research
Aravind Joshi | Mitch Marcus | Mark Steedman | Bonnie Webber
Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27,1990

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Narrated Animation: A Case for Generation
Norman Badler | Mark Steedman | Bonnie Lynn Webber
Proceedings of the Fifth International Workshop on Natural Language Generation

1989

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Natural Language Research
Aravind Joshi | Mitch Marcus | Mark Steedman | Bonnie Webber
Speech and Natural Language: Proceedings of a Workshop Held at Philadelphia, Pennsylvania, February 21-23, 1989

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Elements of a Computational Model of Cooperative Response Generation
Brant A. Cheikes | Bonnie L. Webber
Speech and Natural Language: Proceedings of a Workshop Held at Philadelphia, Pennsylvania, February 21-23, 1989

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Natural Language I
Bonnie Lynn Webber
Speech and Natural Language: Proceedings of a Workshop Held at Cape Cod, Massachusetts, October 15-18, 1989

1988

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Foreword to Special Issue on Tense and Aspect
Bonnie Lynn Webber
Computational Linguistics, Volume 14, Number 2, June 1988

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Tense as Discourse Anaphor
Bonnie Lynn Webber
Computational Linguistics, Volume 14, Number 2, June 1988

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Discourse Deixis: Reference to Discourse Segments
Bonnie Lynn Webber
26th Annual Meeting of the Association for Computational Linguistics

1987

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The Interpretation of Tense in Discourse
Bonnie Lynn Webber
25th Annual Meeting of the Association for Computational Linguistics

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Position Paper: Event Reference
Bonnie Lynn Webber
Theoretical Issues in Natural Language Processing 3

1986

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Research in Natural Language Processing
Aravind Joshi | Tim Finin | Dale Miller | Lokendra Shastri | Bonnie Webber
Strategic Computing - Natural Language Workshop: Proceedings of a Workshop Held at Marina del Rey, California, May 1-2, 1986

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Living Up to Expectations: Computing Expert Responses
Aravind Joshi | Bonnie Webber | Ralph M. Weischedel
Strategic Computing - Natural Language Workshop: Proceedings of a Workshop Held at Marina del Rey, California, May 1-2, 1986

1984

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Preventing False Inferences
Aravind Joshi | Bonnie Webber | Ralph M. Weischedel
10th International Conference on Computational Linguistics and 22nd Annual Meeting of the Association for Computational Linguistics

1982

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Taking the Initiative in Natural Language Data Base Interactions: Justifying Why
Bonnie Webber | Aravind Joshi
Coling 1982: Proceedings of the Ninth International Conference on Computational Linguistics

1981

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Some Issues in Parsing and Natural Language Understanding
Robert J. Bobrow | Bonnie L. Webber
19th Annual Meeting of the Association for Computational Linguistics

1980

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Interactive Discourse: Looking to the Future: Panel Chair’s Introduction
Bonnie Lynn Webber
18th Annual Meeting of the Association for Computational Linguistics

1978

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Description Formation and Discourse Model Synthesis
Bonnie Lynn Webber
American Journal of Computational Linguistics (December 1978)

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Description Formation and Discourse Model Synthesis
Bonnie Lynn Webber
Theoretical Issues in Natural Language Processing-2

1975

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Theoretical Issues in Natural Language Processing: Supplement
B.L. Nash-Webber | Roger Schank
Theoretical Issues in Natural Language Processing: Supplement

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Theoretical Issues in Natural Language Processing
B.L. Nash-Webber | Roger Schank
Theoretical Issues in Natural Language Processing

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