Joint Event Extraction via Structural Semantic Matching
원문 초록
Event Extraction (EE) is one of the essential tasks in information extraction, which aims to detect event mentions from text and find the corresponding argument roles. The EE task can be abstracted as a process of matching the semantic definitions and argument structures of event types with the target text. This paper encodes the semantic features of event types and makes structural matching with target text. Specifically, Semantic Type Embedding (STE) and Dynamic Structure Encoder (DSE) modules are proposed. Also, the Joint Structural Semantic Matching (JSSM) model is built to jointly perform event detection and argument extraction tasks through a bidirectional attention layer. The experimental results on the ACE2005 dataset indicate that our model achieves a significant performance improvement
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction
EnrichEvent: Enriching Social Data with Contextual Information for Emerging Event Extraction
The Devil is in the Details: On the Pitfalls of Event Extraction Evaluation
Enhancing Event Extraction from Short Stories through Contextualized Prompts
Debate as Optimization: Adaptive Conformal Prediction and Diverse Retrieval for Event Extraction
Decompose, Enrich, and Extract! Schema-aware Event Extraction using LLMs
토론
이 논문과 연결된 포럼 글이 아직 없습니다.