@inproceedings{wilner-etal-2021-narrative,
title = "Narrative Embedding: {R}e-{C}ontextualization Through Attention",
author = "Wilner, Sean and
Woolridge, Daniel and
Glick, Madeleine",
editor = "Moens, Marie-Francine and
Huang, Xuanjing and
Specia, Lucia and
Yih, Scott Wen-tau",
booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
month = nov,
year = "2021",
address = "Online and Punta Cana, Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.emnlp-main.105",
doi = "10.18653/v1/2021.emnlp-main.105",
pages = "1393--1405",
abstract = "Narrative analysis is becoming increasingly important for a number of linguistic tasks including summarization, knowledge extraction, and question answering. We present a novel approach for narrative event representation using attention to re-contextualize events across the whole story. Comparing to previous analysis we find an unexpected attachment of event semantics to predicate tokens within a popular transformer model. We test the utility of our approach on narrative completion prediction, achieving state of the art performance on Multiple Choice Narrative Cloze and scoring competitively on the Story Cloze Task.",
}
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<abstract>Narrative analysis is becoming increasingly important for a number of linguistic tasks including summarization, knowledge extraction, and question answering. We present a novel approach for narrative event representation using attention to re-contextualize events across the whole story. Comparing to previous analysis we find an unexpected attachment of event semantics to predicate tokens within a popular transformer model. We test the utility of our approach on narrative completion prediction, achieving state of the art performance on Multiple Choice Narrative Cloze and scoring competitively on the Story Cloze Task.</abstract>
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%0 Conference Proceedings
%T Narrative Embedding: Re-Contextualization Through Attention
%A Wilner, Sean
%A Woolridge, Daniel
%A Glick, Madeleine
%Y Moens, Marie-Francine
%Y Huang, Xuanjing
%Y Specia, Lucia
%Y Yih, Scott Wen-tau
%S Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and Punta Cana, Dominican Republic
%F wilner-etal-2021-narrative
%X Narrative analysis is becoming increasingly important for a number of linguistic tasks including summarization, knowledge extraction, and question answering. We present a novel approach for narrative event representation using attention to re-contextualize events across the whole story. Comparing to previous analysis we find an unexpected attachment of event semantics to predicate tokens within a popular transformer model. We test the utility of our approach on narrative completion prediction, achieving state of the art performance on Multiple Choice Narrative Cloze and scoring competitively on the Story Cloze Task.
%R 10.18653/v1/2021.emnlp-main.105
%U https://aclanthology.org/2021.emnlp-main.105
%U https://doi.org/10.18653/v1/2021.emnlp-main.105
%P 1393-1405
Markdown (Informal)
[Narrative Embedding: Re-Contextualization Through Attention](https://aclanthology.org/2021.emnlp-main.105) (Wilner et al., EMNLP 2021)
ACL
- Sean Wilner, Daniel Woolridge, and Madeleine Glick. 2021. Narrative Embedding: Re-Contextualization Through Attention. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 1393–1405, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.