AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library
Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera, Gemma Boleda
Abstract
This paper describes our winning contribution to SemEval 2018 Task 4: Character Identification on Multiparty Dialogues. It is a simple, standard model with one key innovation, an entity library. Our results show that this innovation greatly facilitates the identification of infrequent characters. Because of the generic nature of our model, this finding is potentially relevant to any task that requires the effective learning from sparse or imbalanced data.- Anthology ID:
- S18-1008
- Volume:
- Proceedings of the 12th International Workshop on Semantic Evaluation
- Month:
- June
- Year:
- 2018
- Address:
- New Orleans, Louisiana
- Venues:
- SemEval | *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 65–69
- Language:
- URL:
- https://aclanthology.org/S18-1008
- DOI:
- 10.18653/v1/S18-1008
- Cite (ACL):
- Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera, and Gemma Boleda. 2018. AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library. In Proceedings of the 12th International Workshop on Semantic Evaluation, pages 65–69, New Orleans, Louisiana. Association for Computational Linguistics.
- Cite (Informal):
- AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library (Aina et al., SemEval-*SEM 2018)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/S18-1008.pdf
- Code
- amore-upf/semeval2018-task4