CLASP
The Centre for Linguistic Theory and Studies in Probability

Disagreements in Anaphoric Interpretation

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 interpretation/coreference. I will present the recently released Phrase Detectives 2.1 corpus, containing around 2 million crowdsourced judgements for more than 100,000 markable, an average of 20 judgements per markable; the Mention Pair Annotation (MPA) Bayesian inference model developed to aggregate these judgements; and the results of a preliminary analysis of disagreements in the corpus suggesting that between 10& % and 30% of marbles in the corpus appear to be genuinely ambiguous.

Joint work with Jon Chamberlain, Silviu Paun, Alexandra Uma, Juntago Yu, Derya Cokal, Janosch Haber, Richard Bartle and Udo Kruschwitz.