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Disagreements in anaphoric interpretation

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The assumption that natural language expressions have a single, discrete and clearly identifiable meaning in a given context, successfully challenged in lexical semantics by the rise of distributional models, nevertheless still underlies much work in computational linguistics, including work based on distributed representations. In this talk I will first of all present the evidence that convinced us that the assumption that a single interpretation can always be assigned to anaphoric expression is no more than a convenient idealization. I will then discuss recent work on the DALI project that aims to develop a new model of interpretation that abandons this assumption for the case of anaphoric interpretaton / coreference. I will present the recently released Phrase Detectives 2.1 corpus, containing around 2 million crowdsourced judgments for more than 100,000 markables, an average of 20 judgments per markable; the Mention Pair Annotation (MPA) Bayesian inference model developed to aggregate these judgments; and the results of a preliminary analysis of disagreements in the corpus suggesting that between 10% and 30% of markables in the corpus appear to be genuinely ambiguous.

Joint work with Jon Chamberlain, Silviu Paun, Alexandra Uma, Juntao Yu, Richard Bartle and Udo Kruschwitz

This talk is part of the Language Technology Lab Seminars series.

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