https://github.com/brownfortress/llms-trc
공식 코드Will LLMs Replace the Encoder-Only Models in Temporal Relation Classification?
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Temporal Relation Classification is the task that is concerned with classifying the temporal relation between a pair of temporal entities (traditional events and temporal expressions). Initial approaches aimed to classify the temporal relation in thirteen relation types that were depicted by James Allen in his seminal work "Maintaining Knowledge about Temporal Intervals". However, due to the ambiguity in the annotation, recent corpora have been limiting the type of relations to a subset of those relations.
Notice that although Temporal Relation Classification can be thought of as a subtask of Temporal Relation Extraction, the two tasks can be morphed if one adds a label that indicates the absence of a temporal relation between the entities (e.g. "no_relation" or "vague") to Temporal Relation Classification.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Will LLMs Replace the Encoder-Only Models in Temporal Relation Classification?
tieval: An Evaluation Framework for Temporal Information Extraction Systems
Word-Level Loss Extensions for Neural Temporal Relation Classification
Extracting Temporal Event Relation with Syntax-guided Graph Transformer
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.