Papers › Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor Detection
Bigrams and BiLSTMs Two Neural Networks for Sequential Metaphor Detection
Yuri Bizzoni, Mehdi Ghanimifard
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.
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