@inproceedings{blair-stanek-van-durme-2022-improved,
title = "Improved Induction of Narrative Chains via Cross-Document Relations",
author = "Blair-stanek, Andrew and
Van Durme, Benjamin",
editor = "Nastase, Vivi and
Pavlick, Ellie and
Pilehvar, Mohammad Taher and
Camacho-Collados, Jose and
Raganato, Alessandro",
booktitle = "Proceedings of the 11th Joint Conference on Lexical and Computational Semantics",
month = jul,
year = "2022",
address = "Seattle, Washington",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.starsem-1.18",
doi = "10.18653/v1/2022.starsem-1.18",
pages = "208--212",
abstract = "The standard approach for inducing narrative chains considers statistics gathered per individual document. We consider whether statistics gathered using cross-document relations can lead to improved chain induction. Our study is motivated by legal narratives, where cases typically cite thematically similar cases. We consider four novel variations on pointwise mutual information (PMI), each accounting for cross-document relations in a different way. One proposed PMI variation performs 58{\%} better relative to standard PMI on recall@50 and induces qualitatively better narrative chains.",
}
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<abstract>The standard approach for inducing narrative chains considers statistics gathered per individual document. We consider whether statistics gathered using cross-document relations can lead to improved chain induction. Our study is motivated by legal narratives, where cases typically cite thematically similar cases. We consider four novel variations on pointwise mutual information (PMI), each accounting for cross-document relations in a different way. One proposed PMI variation performs 58% better relative to standard PMI on recall@50 and induces qualitatively better narrative chains.</abstract>
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%0 Conference Proceedings
%T Improved Induction of Narrative Chains via Cross-Document Relations
%A Blair-stanek, Andrew
%A Van Durme, Benjamin
%Y Nastase, Vivi
%Y Pavlick, Ellie
%Y Pilehvar, Mohammad Taher
%Y Camacho-Collados, Jose
%Y Raganato, Alessandro
%S Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
%D 2022
%8 July
%I Association for Computational Linguistics
%C Seattle, Washington
%F blair-stanek-van-durme-2022-improved
%X The standard approach for inducing narrative chains considers statistics gathered per individual document. We consider whether statistics gathered using cross-document relations can lead to improved chain induction. Our study is motivated by legal narratives, where cases typically cite thematically similar cases. We consider four novel variations on pointwise mutual information (PMI), each accounting for cross-document relations in a different way. One proposed PMI variation performs 58% better relative to standard PMI on recall@50 and induces qualitatively better narrative chains.
%R 10.18653/v1/2022.starsem-1.18
%U https://aclanthology.org/2022.starsem-1.18
%U https://doi.org/10.18653/v1/2022.starsem-1.18
%P 208-212
Markdown (Informal)
[Improved Induction of Narrative Chains via Cross-Document Relations](https://aclanthology.org/2022.starsem-1.18) (Blair-stanek & Van Durme, *SEM 2022)
ACL