Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor Detection
2018-06-01WS 2018Code Available0· sign in to hype
Yuri Bizzoni, Mehdi Ghanimifard
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Abstract
We present and compare two alternative deep neural architectures to perform word-level metaphor detection on text: a bi-LSTM model and a new structure based on recursive feed-forward concatenation of the input. We discuss different versions of such models and the effect that input manipulation - specifically, reducing the length of sentences and introducing concreteness scores for words - have on their performance.