Cross-document Event Coreference Search: Task, Dataset and Modeling

• URL: http://arxiv.org/abs/2210.12654v1
• Date: Sun, 23 Oct 2022 08:21:25 GMT
• Title: Cross-document Event Coreference Search: Task, Dataset and Modeling
• Authors: Alon Eirew, Avi Caciularu, Ido Dagan
• Abstract summary: We propose an appealing, and often more applicable, complementary set up for the task - Cross-document Coreference Search. To support research on this task, we create a corresponding dataset, which is derived from Wikipedia. We present a novel model that integrates a powerful coreference scoring scheme into the DPR architecture, yielding improved performance.
• Score: 26.36068336169796
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The task of Cross-document Coreference Resolution has been traditionally formulated as requiring to identify all coreference links across a given set of documents. We propose an appealing, and often more applicable, complementary set up for the task - Cross-document Coreference Search, focusing in this paper on event coreference. Concretely, given a mention in context of an event of interest, considered as a query, the task is to find all coreferring mentions for the query event in a large document collection. To support research on this task, we create a corresponding dataset, which is derived from Wikipedia while leveraging annotations in the available Wikipedia Event Coreference dataset (WEC-Eng). Observing that the coreference search setup is largely analogous to the setting of Open Domain Question Answering, we adapt the prominent Deep Passage Retrieval (DPR) model to our setting, as an appealing baseline. Finally, we present a novel model that integrates a powerful coreference scoring scheme into the DPR architecture, yielding improved performance.

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