Free the Plural: Unrestricted Split-Antecedent Anaphora Resolution (2020)

Abstract: Now that the performance of coreference resolvers on the simpler forms of anaphoric reference has greatly improved, more attention is devoted to more complex aspects of anaphora. One limitation of virtually all coreference resolution models is the focus on single-antecedent anaphors. Plural anaphors with multiple antecedents-so-called split-antecedent anaphors (as in John met Mary. They went to the movies) have not been widely studied, because they are not annotated in ONTONOTES and are relatively infrequent in other corpora. In this paper, we introduce the first model for unrestricted resolution of split-antecedent anaphors. We start with a strong baseline enhanced by BERT embeddings, and show that we can substantially improve its performance by addressing the sparsity issue. To do this, we experiment with auxiliary corpora where split-antecedent anaphors were annotated by the crowd, and with transfer learning models using element-of bridging references and single-antecedent coreference as auxiliary tasks. Evaluation on the gold annotated ARRAU corpus shows that the out best model uses a combination of three auxiliary corpora achieved F1 scores of 70% and 43.6% when evaluated in a lenient and strict setting, respectively, i.e., 11 and 21 percentage points gain when compared with our baseline.

## experiments datasets we evaluated our models on the arrau corpus @xcite as this is the only gold annotated corpus with split-antecedent anaphors annotated. 8 the corpus also contains annotations of the bridging references and single-antecedent coreference relations used for the auxiliary datasets. we used all four subcorpora of arrau: rst (news), trains (dialogue), pear (fiction) and gnome (medical and art history). 301 out of 552 total documents contain splitantecedent anaphors. we use the 1-7th, 8th, 9-10th of every 10 documents as our train, dev and test dataset, respectively (see in addition, we used the phrase detectives corpus to create auxiliary datasets. the pd corpus contains 542 documents from two main domains, wikipedia and fiction. 165 documents contain split-antecedent anaphors according to the silver labels in the corpus; we use those documents as our pd-silver corpus. our pd-crowd auxiliary corpus consists of the 467 documents which contain split antecedents when aggregated as described in section 3.2. the element-of corpus has 213 documents contain element-of bridging relations from the non-dev/test portion of the arrau corpus. the single-coref corpus is formed by 462 non-dev/test documents of the arrau corpus. evaluation metrics following @xcite we report lenient f1 scores that give partial credit when only some of the split individual antecedents of a plural are found, and consider an antecedent correct as long as it belongs to the correct gold single-antecedent cluster. we further report strict scores that require all antecedents of split-antecedent anaphors be correctly resolved for the final evaluation. hyperparameters we used the default settings from @xcite , replacing their elmo settings with the bert settings from @xcite . we trained the models (including pre-training models) for 200k steps. ## other approaches to split-antecedent anaphora resolution recently, @xcite introduced the first modern system to resolve split antecedent anaphora, although focusing only on plural pronouns they and them, and using a corpus of fiction they themselves annotated. @xcite proposed a learning-based system using handcrafted features, which achieved a score of 43.4% using the lenient evaluation they proposed and we adopted. the version of the task tackled in this paper is harder in three respects. first, our system resolves all split-antecedent references, without restriction. secondly, our system was evaluated on the full arrau corpus @xcite , which contains text from multiple genres (news, dialogues, stories, medical and art history).