STEMLE, Egon and Alexander ONYSKO. Testing the role of metadata in metaphor identification. In The Second Workshop on Figurative Language Processing. 2020.
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Basic information
Original name Testing the role of metadata in metaphor identification
Authors STEMLE, Egon and Alexander ONYSKO.
Edition The Second Workshop on Figurative Language Processing, 2020.
Other information
Original language English
Type of outcome Presentations at conferences
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Organization unit Faculty of Informatics
Tags International impact
Changed by Changed by: Egon Stemle, M.Sc., učo 501885. Changed: 31/8/2020 20:52.
Abstract
Background: Previous research has shown a positive information gain when using word embeddings from learner corpus data for metaphor classification in a neural network (Stemle & Onysko, 2018) Aim: Explore the potential influence of the data structure in the annotated part of the ETS Corpus of Non-Native written English; particular focus on: proficiency ratings, essay prompt and L1 of the learner System: fastText word embeddings from different corpora in a bi-directional recursive neural network with long-term short-term memory (LSTM BiRNN); a flat sequence to sequence neural network with one hidden layer using TensorFlow+Keras (Abadi et al., 2015) in Python.
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