Event coreference identifies when different mentions refer to the same event — recognizing that "the attack," "the incident," and "it" all refer to the same event, enabling coherent event tracking across documents and building unified event representations.

What Is Event Coreference?

• Definition: Determine when event mentions refer to same real-world event.
• Example: "The merger" and "the acquisition" may refer to same event.
• Goal: Link all mentions of same event for unified representation.

Event Mention Types

Explicit: Clear event description ("the earthquake"). Pronominal: Pronouns ("it," "that"). Nominal: Noun phrases ("the incident," "the tragedy"). Verbal: Verb phrases ("happened," "occurred"). Implicit: Event implied but not stated.

Why Event Coreference?

• Information Fusion: Combine information from multiple mentions.
• Timeline Construction: Avoid duplicate events in timelines.
• Cross-Document: Track same event across news articles.
• Knowledge Graphs: Create unified event nodes.
• Summarization: Avoid redundant event descriptions.

Coreference Signals

Lexical: Same or similar words ("attack" / "assault"). Temporal: Same time references. Spatial: Same location. Participants: Same entities involved. Event Type: Same event category. Discourse: Pronouns, definite descriptions.

Challenges

Ambiguity: Similar events that are actually different. Granularity: Is "World War II" one event or many? Cross-Document: Matching events across sources. Partial Overlap: Events that partially overlap. Implicit Mentions: Recognizing implicit event references.

AI Techniques: Clustering, pairwise classification, graph-based methods, neural coreference models, joint entity-event coreference.

Applications: Multi-document summarization, news aggregation, knowledge base construction, question answering, event tracking.

Datasets: ECB+, KBP Event Nugget, TAC-KBP Event Track.

Tools: Research event coreference systems, extensions of entity coreference tools.