WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia
Cross-document event coreference resolution is a foundational task for NLP applications involving multi-text processing. However, existing corpora for this task are scarce and relatively small, while annotating only modest-size clusters of documents belonging to the same topic. To complement these resources and enhance future research, we present Wikipedia Event Coreference (WEC), an efficient methodology for gathering a large-scale dataset for cross-document event coreference from Wikipedia, where coreference links are not restricted within predefined topics. We apply this methodology to the English Wikipedia and extract our large-scale WEC-Eng dataset. Notably, our dataset creation method is generic and can be applied with relatively little effort to other Wikipedia languages. To set baseline results, we develop an algorithm that adapts components of state-of-the-art models for within-document coreference resolution to the cross-document setting. Our model is suitably efficient and outperforms previously published state-of-the-art results for the task.
Code (2)
Tasks
coreference-resolutionCoreference ResolutionEvent Coreference ResolutionSimilar Papers 제목 키워드 기반
DocEE: A Large-Scale Dataset for Document-level Event Extraction
Event extraction (EE) is the task of identifying events and their types, along with the involved arguments. Despite the great success in sentence-level event extraction, events are more naturally presented in the form of…
Document-level Event ExtractionEvent ExtractionSentenceEnhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information
Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such as location, time, agent, and patient), …
coreference-resolutionCoreference ResolutionEvent Coreference ResolutionEventSum: A Large-Scale Event-Centric Summarization Dataset for Chinese Multi-News Documents
In real life, many dynamic events, such as major disasters and large-scale sports events, evolve continuously over time. Obtaining an overview of these events can help people quickly understand the situation and respond …
Document SummarizationMulti-Document SummarizationDocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction
Event extraction aims to identify an event and then extract the arguments participating in the event. Despite the great success in sentence-level event extraction, events are more naturally presented in the form of docum…
Document-level Event ExtractionEvent ExtractionSentenceDocEE: A Large-Scale and Fine-grained Benchmark for Document-level Event Extraction
Event extraction aims to identify an event and then extract the arguments participating in the event. Despite the great success in sentence-level event extraction, events are more naturally presented in the form of docum…
Document-level Event ExtractionEvent ExtractionSentence