Event Causality Insights Through AI
K Jahnavi, Venkat Saladi, D. Deepa · 2025
The objective is to identify the relationship between causes and their effects within the text. The aim is to automate the recognition of valuable cause-effect relationships. Advanced algorithms such as LSTM and Causal BERT are employed to detect these relationships. Supervised algorithms can effectively extract cause and effect conclusions due to their reliance on labeled datasets for training. Accurate identification of "C" (cause), "E" (effect), and the tag "Emb" (Embedded Causation) is essential for extracting these relationships from the text.