Yuchen Zhang and Nianwen Xue. 2018. Structured Interpretation of Temporal Relations. In Proceedings of the 11th Language Resources and Evaluation Conference (LREC-2018), Miyazaki, Japan
Temporal relations between events and time expressions in a document are often modeled in an unstructured manner where relations between individual pairs of time expressions and events are considered in isolation. This often results in inconsistent and incomplete annotation and computational modeling. We propose a novel annotation approach where events and time expressions in a document form a dependency tree in which each dependency relation corresponds to an instance of temporal anaphora where the antecedent is the parent and the anaphor is the child. We annotate a corpus of 235 documents using this approach in the two genres of news and narratives, with 48 documents doubly annotated. We report a stable and high inter-annotator agreement on the doubly annotated subset, validating our approach, and perform a quantitative comparison between the two genres of the entire corpus. We make this corpus publicly available.
Lunguage: A Benchmark for Structured and Sequential Chest X-ray Interpretation
KAIST（韩国科学技术院）；Ghent University（根特大学）；Seoul National University Hospital（首尔国立大学医院）；Seoul Medical Center（首尔医院）；Yeungnam University College of Medicine（延世大学医学院）；Microsoft Research Health Futures（微软研究院健康未来）
Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction
Information Sciences Institute, University of Southern California（南加州大学信息科学研究所）；Department of Computer Science, University of Southern California（南加州大学计算机科学系）；Department of Computer Science, University of California, Los Angeles（加州大学洛杉矶分校计算机科学系）
