CauseNet: Towards a Causality Graph Extracted from the Web
Knowledge-Augmented Language Models for Cause-Effect Relation Classification https://arxiv.org/abs/2112.08615
Exploratory study on Cervical Cancer: verifying known causal relations and assessing risk factors from women medical history datasets.
The aim of the project is to perform joint classification of temporal and causal relations between two events that appear in text. We built an LSTM model that makes use of the POS tags and dependency structures in the text to classify temporal and causal relations.
CauseNet: Towards a Causality Graph Extracted from the Web
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