@inproceedings{kobayashi-malon-2022-analyzing,
title = "Analyzing Coreference and Bridging in Product Reviews",
author = "Kobayashi, Hideo and
Malon, Christopher",
editor = "Ogrodniczuk, Maciej and
Pradhan, Sameer and
Nedoluzhko, Anna and
Ng, Vincent and
Poesio, Massimo",
booktitle = "Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.crac-1.3",
pages = "22--30",
abstract = "Product reviews may have complex discourse including coreference and bridging relations to a main product, competing products, and interacting products. Current approaches to aspect-based sentiment analysis (ABSA) and opinion summarization largely ignore this complexity. On the other hand, existing systems for coreference and bridging were trained in a different domain. We collect mention type annotations relevant to coreference and bridging for 498 product reviews. Using these annotations, we show that a state-of-the-art factuality score fails to catch coreference errors in product reviews, and that a state-of-the-art coreference system trained on OntoNotes does not perform nearly as well on product mentions. As our dataset grows, we expect it to help ABSA and opinion summarization systems to avoid entity reference errors.",
}
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<abstract>Product reviews may have complex discourse including coreference and bridging relations to a main product, competing products, and interacting products. Current approaches to aspect-based sentiment analysis (ABSA) and opinion summarization largely ignore this complexity. On the other hand, existing systems for coreference and bridging were trained in a different domain. We collect mention type annotations relevant to coreference and bridging for 498 product reviews. Using these annotations, we show that a state-of-the-art factuality score fails to catch coreference errors in product reviews, and that a state-of-the-art coreference system trained on OntoNotes does not perform nearly as well on product mentions. As our dataset grows, we expect it to help ABSA and opinion summarization systems to avoid entity reference errors.</abstract>
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%0 Conference Proceedings
%T Analyzing Coreference and Bridging in Product Reviews
%A Kobayashi, Hideo
%A Malon, Christopher
%Y Ogrodniczuk, Maciej
%Y Pradhan, Sameer
%Y Nedoluzhko, Anna
%Y Ng, Vincent
%Y Poesio, Massimo
%S Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference
%D 2022
%8 October
%I Association for Computational Linguistics
%C Gyeongju, Republic of Korea
%F kobayashi-malon-2022-analyzing
%X Product reviews may have complex discourse including coreference and bridging relations to a main product, competing products, and interacting products. Current approaches to aspect-based sentiment analysis (ABSA) and opinion summarization largely ignore this complexity. On the other hand, existing systems for coreference and bridging were trained in a different domain. We collect mention type annotations relevant to coreference and bridging for 498 product reviews. Using these annotations, we show that a state-of-the-art factuality score fails to catch coreference errors in product reviews, and that a state-of-the-art coreference system trained on OntoNotes does not perform nearly as well on product mentions. As our dataset grows, we expect it to help ABSA and opinion summarization systems to avoid entity reference errors.
%U https://aclanthology.org/2022.crac-1.3
%P 22-30
Markdown (Informal)
[Analyzing Coreference and Bridging in Product Reviews](https://aclanthology.org/2022.crac-1.3) (Kobayashi & Malon, CRAC 2022)
ACL
- Hideo Kobayashi and Christopher Malon. 2022. Analyzing Coreference and Bridging in Product Reviews. In Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference, pages 22–30, Gyeongju, Republic of Korea. Association for Computational Linguistics.