Learning to Represent Words in Context with Multilingual Supervision

14 Nov 2015 Kazuya Kawakami Chris Dyer

We present a neural network architecture based on bidirectional LSTMs to compute representations of words in the sentential contexts. These context-sensitive word representations are suitable for, e.g., distinguishing different word senses and other context-modulated variations in meaning... (read more)

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