| Challenge: | Recent neural approaches to event temporal relation extraction map events to embeddings in the Euclidean space and train a classifier to detect temporal relations between event pairs. |
| Approach: | They propose to embed events into hyperbolic spaces to model hierarchical structures . they propose to use hyperbolical embeddings to directly infer event relations . |
| Outcome: | The proposed architecture is based on two approaches to encode events and their temporal relations in hyperbolic spaces. |
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| Challenge: | Existing methods for temporal relations and event durations are insufficient for determining the fine-grained temporal structure of complex events. |
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Knowledge Association with Hyperbolic Knowledge Graph Embeddings (2020.emnlp-main)
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| Challenge: | Existing methods for knowledge graphs (KGs) depend on high embedding dimensions and hierarchical structures to achieve expressiveness. |
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Multi-Relational Hyperbolic Word Embeddings from Natural Language Definitions (2024.eacl-long)
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| Challenge: | a fundamental characteristic of natural language definitions is that they are widely abundant, pos-1. |
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An Improved Neural Baseline for Temporal Relation Extraction (D19-1)
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| Challenge: | Existing datasets are small and/or have low inter-annotator agreements. |
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| Challenge: | Existing systems treat this task as a pipeline of two separate subtasks, i.e., event extraction and temporal relation classification. |
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Severing the Edge Between Before and After: Neural Architectures for Temporal Ordering of Events (2020.emnlp-main)
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Miguel Ballesteros, Rishita Anubhai, Shuai Wang, Nima Pourdamghani, Yogarshi Vyas, Jie Ma, Parminder Bhatia, Kathleen McKeown, Yaser Al-Onaizan
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HyILR: Hyperbolic Instance-Specific Local Relationships for Hierarchical Text Classification (2025.acl-srw)
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| Challenge: | Hierarchical text classification models rely on capturing global label hierarchy, which contains static and redundant relationships. |
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More than Classification: A Unified Framework for Event Temporal Relation Extraction (2023.acl-long)
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| Challenge: | Existing methods for event temporal relation extraction ignore meaning of relations and wipe out their intrinsic dependency. |
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Temporal Information Extraction by Predicting Relative Time-lines (D18-1)
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| Challenge: | a new paradigm for temporal information extraction from text evades the relation extraction phase because there are n 2 possible entity pairs in a text with n temporal entities. |
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