SemEval-2007 Task 15: TempEval Temporal Relation Identification

By Marc Verhagen, Robert J. Gaizauskas, Frank Schilder, Mark Hepple, G. Katz, James Pustejovsky. International Workshop on Semantic Evaluation, 2007

393 citations recorded by the source corpus.

The TempEval task proposes a simple way to evaluate automatic extraction of temporal relations. It avoids the pitfalls of evaluating a graph of inter-related labels by defining three sub tasks that allow pairwise evaluation of temporal relations. The task not only allows straightforward evaluation, it also avoids the complexities of full temporal parsing.

Subfields: Artificial Intelligence, Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/ce428501603cc8f904038a08bc1897cdc589f098

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In Artificial Intelligence

1. Nanyun Peng
2. Dan Roth
3. Rujun Han
4. Qiang Ning
5. Hao Wu
6. Yejin Choi
7. Xiang Ren
8. Lyle Ungar

In Computer Networks and Communications

1. Qiang Ning
2. Rujun Han
3. Nanyun Peng
4. Dan Roth
5. Hao Wu
6. Nathanael Chambers
7. James Pustejovsky
8. Aram Galstyan

Citations in the corpus

• SemEval-2016 Task 12: Clinical TempEval (2016, background): “The TempEval shared tasks have, since 2007, provided a focus for research on temporal information extraction (Verhagen et al., 2007; Verhagen et al., 2010; UzZaman et al., 2013).”
• Domain Knowledge Empowered Structured Neural Net for End-to-End Event Temporal Relation Extraction (2020, neutral): “Early work on temporal relation extraction use local pair-wise classification with hand-engineered features (Mani et al., 2006; Verhagen et al., 2007; Chambers et al., 2007; Ver-hagen and Pustejovsky, 2008).”
• SemEval-2015 Task 6: Clinical TempEval (2015, background): “The TempEval shared tasks have, since 2007, provided a focus for research on temporal information extraction (Verhagen et al., 2007; Verhagen et al., 2010; UzZaman et al., 2013).”
• Dense Event Ordering with a Multi-Pass Architecture (2014, background): “The TempEval competitions (Verhagen et al., 2007; Ver-hagen et al., 2010; UzZaman et al., 2013b) aimed to improve coverage by annotating relations between all events and times in the same sentence.”
• Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction (2019, background): “Early attempts on temporal relation extraction use local pair-wise classification with handengineered features (Mani et al., 2006; Verhagen et al., 2007; Chambers et al., 2007; Verhagen and Pustejovsky, 2008).”
• SemEval-2010 Task 13: TempEval-2 (2010, methodology): “However, the syntactic locality restriction in task C was not present in TempEval-1.”
• A Multi-Axis Annotation Scheme for Event Temporal Relations (2018, background): “…number of TempRel datasets have been collected, including but not limited to the verb-clause augmentation to TB (Bethard et al., 2007), TempEval1-3 (Verhagen et al., 2007, 2010; UzZa-man et al., 2013), TimeBank-Dense (TB-Dense) (Cassidy et al., 2014), EventTimeCorpus (Reimers et al., 2016), and…”
• SemEval-2017 Task 12: Clinical TempEval (2017, methodology): “The TempEval shared tasks have, since 2007, provided a focus for research on temporal information extraction (Verhagen et al., 2007, 2010; UzZaman et al., 2013).”
• Joint Reasoning for Temporal and Causal Relations (2018, methodology): “Multiple datasets with temporal annotations are available thanks to the TempEval (TE) workshops (Verhagen et al., 2007, 2010; UzZaman et al., 2013).”
• Extracting Human Temporal Orientation from Facebook Language (2015, background): “The SemEval competitions have provided data sets that facilitate the comparison of different meth-ods for evaluating time expressions, events, and temporal relations (Verhagen et al., 2007; Verhagen et al., 2010; UzZaman et al., 2013).”
• Extracting Temporal Event Relation with Syntactic-Guided Temporal Graph Transformer (2021, background): “Early studies on temporal relation extraction mainly model it as a pairwise classification problem (Mani et al., 2006a; Verhagen et al., 2007; Verhagen and Pustejovsky, 2008; Verhagen et al., 2010; Bethard et al., 2016; MacAvaney et al., 2017) and use statistical machine learning techniques with…”
• Joint Inference for Event Timeline Construction (2012, methodology): “This corpus was later used (with simplifications) in two TempEval challenges (Verhagen et al., 2007; Verhagen et al., 2010).”
• Deep Structured Neural Network for Event Temporal Relation Extraction (2019, background): “The series of TempEval competitions (Verhagen et al., 2007, 2010; UzZaman et al., 2013) attract many research interests in predicting event temporal relations.”
• HiEve: A Corpus for Extracting Event Hierarchies from News Stories (2014, methodology): “Much of this work was carried out within designated evaluation campaigns such as Automated Content Extraction (ACE) (ACE, 2005; ACE, 2007) and TempEval (Verhagen et al., 2007; Verhagen et al., 2010; UzZaman et al., 2013).”
• Contextualized Word Embeddings Enhanced Event Temporal Relation Extraction for Story Understanding (2019, background): “The series of TempEval competitions (Verhagen et al., 2007, 2010; UzZaman et al., 2013)”