Event-Related Features in Feedforward Neural Networks Contribute to Identifying Implicit Causal Relations in Discourse

Edoardo Ponti & Anna-Leena Korhonen
Causal relations play a key role in information extraction and reasoning. Most of the times, their expression is ambiguous or implicit, i.e. without signals in the text. This makes their identification challenging. We aim to improve their identification by implementing a Feedforward Neural Network with a novel set of features for this task. In particular, these are based on the position of event mentions and the semantics of events and participants. The resulting classifier outperforms...
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