Bootstrapping path-based pronoun resolution

Bergsma, Shane; Lin, Dekang

doi:10.3115/1220175.1220180

Cited by 79 publications

(79 citation statements)

References 16 publications

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“…More precisely, we took the three lists of unigrams (one for each gender) from the Stanford Core NLP Toolkit (Manning et al, 2014) that was compiled from the Bergsma and Lin (2006) gender information to annotate each token of a mention in our corpus with gender if it occurred in one of the lists. Then we propagated the gender of the head token to the entire mention.…”

Section: B Gender and Number Annotationmentioning

confidence: 99%

A Computational Model of Human Preferences for Pronoun Resolution

Seminck

Amsili

2017

Proceedings of the Student Research Workshop at the 15th Conference Of the European Chapter of the Association for Co

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We present a cognitive computational model of pronoun resolution that reproduces the human interpretation preferences of the Subject Assignment Strategy and the Parallel Function Strategy. Our model relies on a probabilistic pronoun resolution system trained on corpus data. Factors influencing pronoun resolution are represented as features weighted by their relative importance. The importance the model gives to the preferences is in line with psycholinguistic studies. We demonstrate the cognitive plausibility of the model by running it on experimental items and simulating antecedent choice and reading times of human participants. Our model can be used as a new means to study pronoun resolution, because it captures the interaction of preferences.

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Section: B Gender and Number Annotationmentioning

confidence: 99%

A Computational Model of Human Preferences for Pronoun Resolution

Seminck

Amsili

2017

Proceedings of the Student Research Workshop at the 15th Conference Of the European Chapter of the Association for Co

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“…The counts were used in order to estimate the gender probability. The story-independent resources that we used are: (a) the U.S. Social Security Administration baby name database (Security, 2014), in which person names are linked with gender and (b) a large name-gender association list developed using a corpus-based bootstrapping approach, which even included the estimated gender for non-person entities (Bergsma and Lin, 2006). For each entity included in (b) a numerical estimate is provided for each gender.…”

Section: Gender Estimationmentioning

confidence: 99%

Proceedings of the 3rd Workshop on Computational Linguistics for Literature (CLFL)

Feldman¹,

Kazantseva²,

Śzpakowicz³

2014

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ii Preface Welcome to the third edition of the workshop on Computational Linguistics for Literature. What started out two years ago as a small affair with an unorthodox title seems to be shaping into a modestly sized but vibrant research community.Thanks to the effort of the authors and the program committee, April 27, 2014 promises to be an interesting day. This year's workshop boasts the rich pickings of papers focussed on creating character representations from text and on applications of such representations. Agarwal et al. present a system for extracting social networks from movie scripts. Coll Ardanuy and Sporleder propose a method of finding similar novels using social networks as the underlying representation. Bullard and Alm work on identifying social information about characters from dialogues in a corpus of plays. Taking this a step further, Iosif and Mishra describe an integrated system for identifying and classifying characters in children's stories based on direct and indirect speech.Taking a complementary point of view, the position paper by Levison and Lessard builds upon their previous work and proposes a graph-based representation for the temporal structure of narratives. The paper by Zemánek and Milička describes a diachronic study of Arabic literature, tracing the influence of certain treatises across centuries.In the categories all of their own are two more papers. Davis and Mohammad break new ground with a paper on generating music from literature; you can listen to a one-minute musical summary of a novel. Mike Kestemont presents a position paper on authorship attribution, a topic which was quite popular in the 2012 and 2013 editions of the workshop.Last but by no means least, we are delighted to have two invited speakers this year. An artist and researcher María Mencía from Kingston University in London will talk about electronic poetry. Jan Christoph Meister from University of Hamburg will tell us about the connections between narratology and computation.We look forward to seeing you in Göteborg. Language-Art Digital Poetics: An exploration of digital textualities in the production of artistic research María Mencía Faculty of Arts and Social Sciences Kingston University AbstractAs an academic and an artist my practice-based research is at the intersection of language, art and digital technology. It explores the area of the in-between, the visual, the aural and the semantic. I am always interested in experimenting with the digital medium with the aim of engaging the reader/viewer/user in an experience of shifting 'in' and 'out' of language. This involves looking 'at' and looking 'through' transparent and abstract textualities and linguistic soundscapes. It draws from avant-garde poetics remediating concepts of reading and writing, exploring digital media grammars (voice activation, use of webcam, use of mouse, acts of revealing, triggering, cut and paste, dragging) for interactivity, aesthetics, engagement and meaning production. It is trans-disciplinary, bringing together different cultu...

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“…This combination feature uses the information similar to the semantic compatibility features proposed by Yang (Yang et al, 2005) and Bergsma (Bergsma and Lin, 2006). Depending on the pronoun type, the feature extractor decides which relationship is used.…”

Section: Semantic Features (Netype)mentioning

confidence: 99%

Exploring domain differences for the design of pronoun resolution systems for biomedical text

Nguyen

Kim

2008

Proceedings of the 22nd International Conference on Computational Linguistics - COLING '08

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Much effort in the research community has been spent on solving the anaphora resolution or pronoun resolution problem, and in particular for news texts. In order to selectively inherit the previous works and solve the same problem for a new domain, we carried out a comparative study with three different corpora: MUC, ACE for the news texts, and GENIA for bio-medical papers. Our corpus analysis and experimental results show the significant differences in the use of pronouns in the two domains, thus by properly considering the characteristics of a domain, we can improve the performance of pronoun resolution for that domain.

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Bootstrapping path-based pronoun resolution

Cited by 79 publications

References 16 publications

A Computational Model of Human Preferences for Pronoun Resolution

A Computational Model of Human Preferences for Pronoun Resolution

Proceedings of the 3rd Workshop on Computational Linguistics for Literature (CLFL)

Exploring domain differences for the design of pronoun resolution systems for biomedical text

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