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
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
65–69
Language:
URL:
https://www.aclweb.org/anthology/S18-1008
DOI:
10.18653/v1/S18-1008
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S18-1008.pdf