@inproceedings{lamarche-langlais-2024-benchie,
title = "{B}ench{IE}{\textasciicircum}{FL}: A Manually Re-Annotated Fact-Based Open Information Extraction Benchmark",
author = "Lamarche, Fabrice and
Langlais, Philippe",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Findings of the Association for Computational Linguistics: ACL 2024",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.findings-acl.496",
doi = "10.18653/v1/2024.findings-acl.496",
pages = "8372--8394",
abstract = "Open Information Extraction (OIE) is a field of natural language processing that aims to present textual information in a format that allows it to be organized, analyzed and reflected upon. Numerous OIE systems are developed, claiming ever-increasing performance, marking the need for objective benchmarks. BenchIE is the latest reference we know of. Despite being very well thought out, we noticed a number of issues we believe are limiting. Therefore, we propose BenchIE{\textasciicircum}FL, a new OIE benchmark which fully enforces the principles of BenchIE while containing fewer errors, omissions and shortcomings when candidate facts are matched towards reference ones. BenchIE{\textasciicircum}FL allows insightful conclusions to be drawn on the actual performance of OIE extractors.",
}
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%0 Conference Proceedings
%T BenchIE⌃FL: A Manually Re-Annotated Fact-Based Open Information Extraction Benchmark
%A Lamarche, Fabrice
%A Langlais, Philippe
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Findings of the Association for Computational Linguistics: ACL 2024
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F lamarche-langlais-2024-benchie
%X Open Information Extraction (OIE) is a field of natural language processing that aims to present textual information in a format that allows it to be organized, analyzed and reflected upon. Numerous OIE systems are developed, claiming ever-increasing performance, marking the need for objective benchmarks. BenchIE is the latest reference we know of. Despite being very well thought out, we noticed a number of issues we believe are limiting. Therefore, we propose BenchIE⌃FL, a new OIE benchmark which fully enforces the principles of BenchIE while containing fewer errors, omissions and shortcomings when candidate facts are matched towards reference ones. BenchIE⌃FL allows insightful conclusions to be drawn on the actual performance of OIE extractors.
%R 10.18653/v1/2024.findings-acl.496
%U https://aclanthology.org/2024.findings-acl.496
%U https://doi.org/10.18653/v1/2024.findings-acl.496
%P 8372-8394
Markdown (Informal)
[BenchIE^FL: A Manually Re-Annotated Fact-Based Open Information Extraction Benchmark](https://aclanthology.org/2024.findings-acl.496) (Lamarche & Langlais, Findings 2024)
ACL