Paraphrasing vs Coreferring: Two Sides of the Same Coin (2020)

Abstract: We study the potential synergy between two different NLP tasks, both confronting predicate lexical variability: identifying predicate paraphrases, and event coreference resolution. First, we used annotations from an event coreference dataset as distant supervision to re-score heuristically-extracted predicate paraphrases. The new scoring gained more than 18 points in average precision upon their ranking by the original scoring method. Then, we used the same re-ranking features as additional inputs to a state-of-the-art event coreference resolution model, which yielded modest but consistent improvements to the model’s performance. The results suggest a promising direction to leverage data and models for each of the tasks to the benefit of the other.

## introduction recognizing that mentions of different lexical predicates discuss the same event is challenging @xcite . lexical resources such as wordnet @xcite capture such synonyms (say, tell) and hypernyms (whisper, talk), as well as antonyms, which can be used to refer to the same event when the arguments are reversed @xcite 0 beat [a] 1 , [a] 1 lose to [a] 0 ). however, wordnet's coverage is insufficient, in particular, missing contextspecific paraphrases (e.g. (hide, launder), in the context of money). conversely, distributional methods enjoy broader coverage, but their precision for this purpose is limited because distributionally similar terms may often be mutually-exclusive (born, die) or may refer to different event types which are only temporally or causally related (sentenced, convicted). two prominent lines of work pertaining to identifying predicates whose meaning or referents can be matched are cross-document (cd) event coreference resolution and recognizing predicate para-tara reid has checked into∨ promises treatment center. actress tara reid entered∨ well-known malibu rehab center. lindsay lohan checked into × rehab in malibu, california. director chris weitz is expected to direct∨ new moon. chris weitz will take on∨ the sequel to "twilight". gary ross is still in negotiations to direct × the sequel. cross-document event coreference resolution systems are typically supervised, usually trained on the ecb+ dataset, which contains clusters of news articles on different topics @xcite . recent systems rely on neural representations of the mentions and their contexts @xcite , while earlier approaches leveraged wordnet and other lexical resources to obtain a signal of whether a pair of mentions may be coreferring (e.g. @xcite . approaches for acquiring predicate paraphrase, in the form of a pair of paraphrastic predicates or predicate templates, were based mostly on unsupervised signals. these included similarity between argument distributions @xcite , backtranslation across languages @xcite @xcite , or leveraging redundant news reports on the same event, which are hence likely to refer to the same events and entities using different words @xcite @xcite @xcite . in some cases, the paraphrase collection phase includes a step of validating a subset of the paraphrases and training a model on these gold paraphrases to re-rank the entire resource @xcite . in this paper, we study the potential synergy between predicate paraphrases and event coreference resolution. we show that the data and models for one task can benefit the other. in one direction (section 3), we use event coreference annotations from the ecb+ dataset as distant supervision to learn an improved scoring of predicate paraphrases in the unsupervised chirps resource @xcite . the distantly supervised scorer significantly improves upon ranking by the original chirps scores, adding 18 points to average precision over a test sample. in the other direction (section 4), we incorporate data from chirps, represented in the chirps re-scorer feature vector, into a state-of-the-art event coreference system @xcite . chirps has a substantial coverage over the ecb+ coreferring mention pairs, and consequently, the incorporation yields a modest but consistent improvement across the various coreference metrics. foot_0 ## background and motivation in this section we provide some background about the cross-document coreference resolution and paraphrase identification (acquisition) tasks, which is relevant for our approaches for synergizing these two tasks. ## chirps*: leveraging coreference information for paraphrasing our goal in this section is to improve paraphrase scoring, in the context of chirps, while leveraging available information and methods for event cross-document coreference resolution. to that end, we introduce chirps*, a new supervised scorer for chirps candidate paraphrases, whose novelties are two fold. first, we extract a richer feature representation for a candidate paraphrase pair (section 3.1), which is fed into a supervised classifier for the candidates. second, we collect, semi-automatically, distantly supervised training data for paraphrase classification, which is derived from the ecb+ cross-document coreference training set, leveraging the close relationship between the two tasks (section 3.2). finally, we provide some implementation details (section 3.3). ## leveraging a paraphrasing resource to improve coreference in section 3 we showed that leveraging cd event coreference annotations and model improves predicate paraphrase ranking. in this section, we show that this co-dependence can be used in both directions, and that using chirps* as an external resource can improve the performance of a cd model. as a preliminary analysis, we computed chirps' coverage of lexically-divergent pairs of co-referring event mentions in ecb+. we found approximately 30% coverage overall and above 50% coverage for coreferring verbal mentions. 4 this indicates a substantial coverage of the lexically-divergent positive coreferrability decisions that need to be made in ecb+. in absolute numbers, chirps covers about 370 lexically-divergent pairs of coreferring event mentions appearing in the ecb+ training set, and about 200 in the test set. ## conclusion and future work we studied the synergy between the tasks of identifying predicate paraphrases and event coreference resolution, both concerned with matching the meanings of lexically-divergent predicates, and showed that they can benefit each other. using event coreference annotations as distant supervision, we learned to re-rank predicate paraphrases that were initially ranked heuristically, and managed to increase their average precision substantially. in the other direction, we incorporated knowledge from our re-ranked predicate paraphrases resource into a model for event coreference resolution, yielding a small improvement upon previous state-of-theart results. we hope that our study will encourage future research to make further progress on both tasks jointly. congle zhang and daniel s weld. 2013. harvesting parallel news streams to generate paraphrases of event relations. in proceedings of the 2013 conference on empirical methods in natural language processing, pages 1776-1786.