1. Transfer Learning for Causal Sentence Detection
- Author
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Kyriakakis, Manolis, Androutsopoulos, Ion, Ametllé, Joan Ginés i, and Saudabayev, Artur
- Subjects
Computer Science - Computation and Language - Abstract
We consider the task of detecting sentences that express causality, as a step towards mining causal relations from texts. To bypass the scarcity of causal instances in relation extraction datasets, we exploit transfer learning, namely ELMO and BERT, using a bidirectional GRU with self-attention (BIGRUATT) as a baseline. We experiment with both generic public relation extraction datasets and a new biomedical causal sentence detection dataset, a subset of which we make publicly available. We find that transfer learning helps only in very small datasets. With larger datasets, BIGRUATT reaches a performance plateau, then larger datasets and transfer learning do not help., Comment: 5 pages, short paper at BioNLP 2019 workshop
- Published
- 2019