SUTime: A library for recognizing and normalizing time expressions
Open accessAbstract
We describe SUTIME, a temporal tagger for recognizing and normalizing temporal expressions in English text.SUTIME is available as part of the Stanford CoreNLP pipeline and can be used to annotate documents with temporal information.It is a deterministic rule-based system designed for extensibility.Testing on the TempEval-2 evaluation corpus shows that this system outperforms state-of-the-art techniques.
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TimeX was compared with a standard benchmark for TIE and normalization (SUTime).
“Additionally, we compared TimeX with a standard benchmark for TIE and normalization (SUTime)56.”
From TimeX: Phenotype Onset Extraction from Clinical Narratives (2026) · cites this paper as [56]
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- References Jenny Rose Finkel, Trond Grenager, and Christopher Manning. 2005. Incorporating non-local information into information ex- traction systems by Gibbs sampling. In Proceedings of the 43nd Annual Meeting of the Association for Computational Linguistics (ACL), pages 363-370.
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- Inderjeet Mani and George Wilson. 2000. Robust temporal pro- cessing of news. In Proceedings of the 38th Annual Meeting on Association for Computational Linguistics, ACL '00, pages 69-76.
- Inderjeet Mani. 2004. Recent developments in temporal infor- mation extraction. In Proceedings of RANLP03, pages 45-60.
- James Pustejovsky, Jos Castao, Robert Ingria, Roser Saur, Robert Gaizauskas, Andrea Setzer, and Graham Katz. 2003. TimeML: Robust specification of event and temporal expressions in text. In in Fifth International Workshop on Computational Seman- tics (IWCS-5.
- Jannik Strötgen and Michael Gertz. 2010. HeidelTime: High quality rule-based extraction and normalization of temporal ex- pressions. In Proceedings of the 5th International Workshop on Semantic Evaluation, pages 321-324.
- Naushad UzZaman and James F. Allen. 2011. Event and tem- poral expression extraction from raw text: first step towards a temporally aware system. International Journal of Semantic Computing.
- Marc Verhagen, Roser Saurí, Tommaso Caselli, and James Puste- jovsky. 2010. SemEval-2010 task 13: TempEval-2. In Pro- ceedings of the 5th International Workshop on Semantic Eval- uation, SemEval '10, pages 57-62. Association for Computa- tional Linguistics.
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Yim, W.-W., Yetisgen, M., Harris, W. P., & Kwan, S. W. (2016) · JAMA Oncology · doi:10.1001/jamaoncol.2016.0213 · Cited by 298 · see citing works
TIMEDIAL: Temporal Commonsense Reasoning in Dialog
Qin, L., Gupta, A., Upadhyay, S., He, L., Choi, Y., & Faruqui, M. (2021) · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · doi:10.18653/v1/2021.acl-long.549 · Cited by 59 · see citing works
TimeX: Phenotype Onset Extraction from Clinical Narratives
Chen, F., Jiang, S., Nguyen, Q. M., Ta, C. N., Wang, K., Chung, W. K., & Weng, C. (2026) · npj Health Systems · doi:10.1038/s44401-026-00099-8
- Authors
- Chang, A. X., & Manning, C.
- Affiliations
- Stanford University (US)
- ORCID
- Manning, Christopher
- Venue
- Proceedings of the Language Resources and Evaluation Conference
- Published
- 2012-05
- Pages
- 3735-3740
- ISSN
- 2522-2686
- OpenAlex
- W2251758222
- Cited by
- 383
- References
- 0
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 5 · 2023: 19 · 2022: 11 · 2021: 34 · 2020: 30 · 2019: 41 · 2018: 37 · 2017: 43 · 2016: 47 · 2015: 39 · 2014: 44 · 2013: 23 · 2012: 2
- FWCI
- 26.50
- Type
- conference paper
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- Language Resources and Evaluation Conference (LREC) (publishedVersion, cc-by-nc)
- Language Resources and Evaluation
- Funders
- Defense Advanced Research Projects Agency (FA8750)
- Advanced Research Projects Agency
- Air Force Research Laboratory (FA8750-09-C-0181)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
- Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Keywords
- temporal expression recognition, temporal expression normalization, temporal tagging, rule-based systems, English text, Stanford CoreNLP, temporal annotation
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