Analyzing Coreference and Bridging in Product Reviews

Hideo Kobayashi, Christopher Malon


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.
Anthology ID:
2022.crac-1.3
Volume:
Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference
Month:
October
Year:
2022
Address:
Gyeongju, Republic of Korea
Venue:
CRAC
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
22–30
Language:
URL:
https://aclanthology.org/2022.crac-1.3
DOI:
Bibkey:
Cite (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.
Cite (Informal):
Analyzing Coreference and Bridging in Product Reviews (Kobayashi & Malon, CRAC 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.crac-1.3.pdf
Dataset:
 2022.crac-1.3.Datasets.zip