AMORE-UPF at SemEval-2018 Task 4: BiLSTM with entity library

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Title:	AMORE-UPF at SemEval-2018 Task 4: BiLSTM with entity library
Author:	Boleda, Gemma; Aina, Laura; Silberer, Carina; Sorodoc, Ionut-Teodor; Westera, Matthijs
Abstract:	Comunicació presentada al 12th International Workshop on Semantic Evaluation (SemEval-2018), celebrat els dies 5 i 6 de juny de 2018 a Nova Orleans, EUA.
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 effective learning from sparse or unbalanced data.
Abstract:	This project has received funding from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 715154), and from the Spanish Ramón y Cajal programme (grant RYC-2015-18907).
Subject(s):	-Computational linguistics -Natural language processing -Computational semantics -Semantic evaluation -Distributional semantics -Reference -Entities
Rights:	© ACL, Creative Commons Attribution 4.0 License http://creativecommons.org/licenses/by/4.0/
Document type:	Conference Object Article - Published version
Published by:	ACL (Association for Computational Linguistics)
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