1 research outputs found
Neural Networks for Cross-lingual Negation Scope Detection
Negation scope has been annotated in several English and Chinese corpora, and
highly accurate models for this task in these languages have been learned from
these annotations. Unfortunately, annotations are not available in other
languages. Could a model that detects negation scope be applied to a language
that it hasn't been trained on? We develop neural models that learn from
cross-lingual word embeddings or universal dependencies in English, and test
them on Chinese, showing that they work surprisingly well. We find that
modelling syntax is helpful even in monolingual settings and that cross-lingual
word embeddings help relatively little, and we analyse cases that are still
difficult for this task.Comment: 8 page