Make Compound Sentences Simple to Analyze: Learning to Split Sentences for Aspect-based Sentiment Analysis
Yongsik Seo, Sungwon Song, Ryang Heo, Jieyong Kim, Dongha Lee
Abstract
In the domain of Aspect-Based Sentiment Analysis (ABSA), generative methods have shown promising results and achieved substantial advancements. However, despite these advancements, the tasks of extracting sentiment quadruplets, which capture the nuanced sentiment expressions within a sentence, remain significant challenges. In particular, compound sentences can potentially contain multiple quadruplets, making the extraction task increasingly difficult as sentence complexity grows. To address this issue, we are focusing on simplifying sentence structures to facilitate the easier recognition of these elements and crafting a model that integrates seamlessly with various ABSA tasks. In this paper, we propose Aspect Term Oriented Sentence Splitter (ATOSS), which simplifies compound sentence into simpler and clearer forms, thereby clarifying their structure and intent. As a plug-and-play module, this approach retains the parameters of the ABSA model while making it easier to identify essential intent within input sentences. Extensive experimental results show that utilizing ATOSS outperforms existing methods in both ASQP and ACOS tasks, which are the primary tasks for extracting sentiment quadruplets- Anthology ID:
- 2024.findings-emnlp.653
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2024
- Month:
- November
- Year:
- 2024
- Address:
- Miami, Florida, USA
- Editors:
- Yaser Al-Onaizan, Mohit Bansal, Yun-Nung Chen
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 11171–11184
- Language:
- URL:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.findings-emnlp.653/
- DOI:
- 10.18653/v1/2024.findings-emnlp.653
- Cite (ACL):
- Yongsik Seo, Sungwon Song, Ryang Heo, Jieyong Kim, and Dongha Lee. 2024. Make Compound Sentences Simple to Analyze: Learning to Split Sentences for Aspect-based Sentiment Analysis. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 11171–11184, Miami, Florida, USA. Association for Computational Linguistics.
- Cite (Informal):
- Make Compound Sentences Simple to Analyze: Learning to Split Sentences for Aspect-based Sentiment Analysis (Seo et al., Findings 2024)
- PDF:
- https://preview.aclanthology.org/build-pipeline-with-new-library/2024.findings-emnlp.653.pdf