Distributional Identification of Non-Referential Pronouns

Proceedings of ACL-08: HLT, pages 10–18, Columbus, Ohio, USA, June 2008. c⃝2008 Association for Computational Linguistics Distributional Identification of Non-Referential Pronouns Shane Bergsma Department of Computing Science University of Alberta Edmonton, Alberta Canada, T6G 2E8 bergsma@cs.ualberta.ca Dekang Lin Google, Inc. 1600 Amphitheatre Parkway Mountain View California, 94301 lindek@google.com Randy Goebel Department of Computing Science University of Alberta Edmonton, Alberta Canada, T6G 2E8 goebel@cs.ualberta.ca Abstract We present an automatic approach to deter- mining whether a pronoun in text refers to a preceding noun phrase or is instead non- referential. We extract the surrounding tex- tual context of the pronoun and gather, from a large corpus, the distribution of words that occur within that context. We learn to reliably classify these distributions as representing ei- ther referential or non-referential pronoun in- stances. Despite its simplicity, experimental results on classifying the English pronoun it show the system achieves the highest perfor- mance yet attained on this important task. 1 Introduction The goal of coreference resolution is to determine which noun phrases in a document refer to the same real-world entity. As part of this task, coreference resolution systems must decide which pronouns re- fer to preceding noun phrases (called antecedents) and which do not. In particular, a long-standing challenge has been to correctly classify instances of the English pronoun it. Consider the sentences: (1) You can make it in advance. (2) You can make it in Hollywood. In sentence (1), it is an anaphoric pronoun refer- ring to some previous noun phrase, like “the sauce” or “an appointment.” In sentence (2), it is part of the idiomatic expression “make it” meaning “succeed.” A coreference resolution system should find an an- tecedent for the first it but not the second. Pronouns that do not refer to preceding noun phrases are called non-anaphoric or non-referential pronouns. The word it is one of the most frequent words in the English language, accounting for about 1% of tokens in text and over a quarter of all third-person pronouns.1 Usually between a quarter and a half of it instances are non-referential (e.g. Section 4, Ta- ble 3). As with other pronouns, the preceding dis- course can affect it’s interpretation. For example, sentence (2) can be interpreted as referential if the preceding sentence is “You want to make a movie?” We show, however, that we can reliably classify a pronoun as being referential or non-referential based solely on the local context surrounding the pronoun. We do this by turning the context into patterns and enumerating all the words that can take the place of it in these patterns. For sentence (1), we can ex- tract the context pattern “make * in advance” and for sentence (2) “make * in Hollywood,” where “*” is a wildcard that can be filled by any token. Non- referential distributions tend to have the word it fill- ing the wildcard position. Referential distributions occur with many other noun phrase fillers. For ex- ample, in our n-gram collection (Section 3.4), “make it in advance” and …

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