AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library

May 14, 2018 ยท Declared Dead ยท ๐Ÿ› International Workshop on Semantic Evaluation

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Authors Laura Aina, Carina Silberer, Ionut-Teodor Sorodoc, Matthijs Westera, Gemma Boleda arXiv ID 1805.05370 Category cs.CL: Computation & Language Citations 4 Venue International Workshop on Semantic Evaluation Last Checked 5 months ago
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.
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