| Challenge: | a cause must occur earlier than its effect, temporal and causal relations are closely related . a joint inference framework is developed for studying temporal, causal relations . |
| Approach: | They propose a joint inference framework for temporal and causal relations . they use constraints inherent in time and causality to enforce constraints . |
| Outcome: | The proposed framework improves extraction of temporal and causal relations from text. |
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| Challenge: | a study aims to identify all the event causal relations in a document, both within a sentence and across sentences . main challenges for achieving comprehensive causal relation identification are sparse among all possible event pairs . few causal relations are explicitly stated, especially for identifying cross-sentence causal relations . |
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| Challenge: | Understanding natural language involves recognizing how multiple event mentions structurally and temporally interact with each other. |
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Amir Feder, Katherine A. Keith, Emaad Manzoor, Reid Pryzant, Dhanya Sridhar, Zach Wood-Doughty, Jacob Eisenstein, Justin Grimmer, Roi Reichart, Margaret E. Roberts, Brandon M. Stewart, Victor Veitch, Diyi Yang
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Conditional Causal Relationships between Emotions and Causes in Texts (2020.emnlp-main)
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Consistent Discourse-level Temporal Relation Extraction Using Large Language Models (2025.findings-emnlp)
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| Challenge: | Recent advances in large language models (LLMs) have spurred research on temporal relation extraction tasks. |
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CReTIHC: Designing Causal Reasoning Tasks about Temporal Interventions and Hallucinated Confoundings (2023.findings-emnlp)
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| Challenge: | Large language models (LLMs) have demonstrated impressive capabilities in natural language processing, but their ability to establish causal relationships remains challenging. |
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