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About Evaluation of F1 Score for RECENT Relation Extraction System

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arxiv 2305.09410 v1 pith:77SA3URF submitted 2023-05-16 cs.CL cs.AI

classification cs.CLcs.AI
keywords evaluationrecentrelationresultscoresystemachievesacl-ijcnlp
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This document contains a discussion of the F1 score evaluation used in the article 'Relation Classification with Entity Type Restriction' by Shengfei Lyu, Huanhuan Chen published on Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021. The authors created a system named RECENT and claim it achieves (then) a new state-of-the-art result 75.2 (previous 74.8) on the TACRED dataset, while after correcting errors and reevaluation the final result is 65.16

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  1. A Grounded and Decomposed Framework for Relation-Level Hallucination Evaluation in Abstractive Summarization

    cs.CL 2026-08 reject novelty 4.0 of 10

    A linguistically refined and normalized index for quantifying relation-level hallucination in abstractive summaries, tested on four models across three datasets.

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