SSN_MLRG1 at SemEval-2022 Task 10: Structured Sentiment Analysis using 2-layer BiLSTM
Karun Anantharaman, Divyasri K, Jayannthan Pt, Angel S, Rajalakshmi Sivanaiah, Sakaya Milton Rajendram, Mirnalinee T T
Abstract
Task 10 in SemEval 2022 is a composite task which entails analysis of opinion tuples, and recognition and demarcation of their nature. In this paper, we will elaborate on how such a methodology is implemented, how it is undertaken for a Structured Sentiment Analysis, and the results obtained thereof. To achieve this objective, we have adopted a bi-layered BiLSTM approach. In our research, a variation on the norm has been effected towards enhancement of accuracy, by basing the categorization meted out to an individual member as a by-product of its adjacent members, using specialized algorithms to ensure the veracity of the output, which has been modelled to be the holistically most accurate label for the entire sequence.Such a strategy is superior in terms of its parsing accuracy and requires less time. This manner of action has yielded an SF1 of 0.33 in the highest-performing configuration.- Anthology ID:
- 2022.semeval-1.184
- Volume:
- Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022)
- Month:
- July
- Year:
- 2022
- Address:
- Seattle, United States
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1324–1328
- Language:
- URL:
- https://aclanthology.org/2022.semeval-1.184
- DOI:
- 10.18653/v1/2022.semeval-1.184
- Cite (ACL):
- Karun Anantharaman, Divyasri K, Jayannthan Pt, Angel S, Rajalakshmi Sivanaiah, Sakaya Milton Rajendram, and Mirnalinee T T. 2022. SSN_MLRG1 at SemEval-2022 Task 10: Structured Sentiment Analysis using 2-layer BiLSTM. In Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), pages 1324–1328, Seattle, United States. Association for Computational Linguistics.
- Cite (Informal):
- SSN_MLRG1 at SemEval-2022 Task 10: Structured Sentiment Analysis using 2-layer BiLSTM (Anantharaman et al., SemEval 2022)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2022.semeval-1.184.pdf
- Data
- MPQA Opinion Corpus, NoReC_fine