Difference between revisions of "Temporal Information Extraction (State of the art)"
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| HeidelTime (t) | | HeidelTime (t) | ||
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| Stro ̈tgen et al., 2013 | | Stro ̈tgen et al., 2013 | ||
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| Chambers, 2013 | | Chambers, 2013 | ||
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| ManTIME (4) | | ManTIME (4) | ||
| − | | | + | | CRF, probabilistic post-processing pipeline, rule-based normaliser |
| Filannino et al., 2013 | | Filannino et al., 2013 | ||
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| Chang et al., 2013 | | Chang et al., 2013 | ||
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| Jung et al., 2013 | | Jung et al., 2013 | ||
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| ClearTK (1,2) | | ClearTK (1,2) | ||
| − | | | + | | SVM, Logistic Regression, third party normaliser |
| Bethard, 2013 | | Bethard, 2013 | ||
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| Kolya et al., 2013 | | Kolya et al., 2013 | ||
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| KUL (2) | | KUL (2) | ||
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| Kolomiyets et al., 2013 | | Kolomiyets et al., 2013 | ||
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| FSS-TimEx | | FSS-TimEx | ||
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| Zavarella et al., 2013 | | Zavarella et al., 2013 | ||
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| − | | | + | | [https://code.google.com/p/cleartk/ Download] |
| − | | | + | | [http://opensource.org/licenses/BSD-3-Clause BSD-3 Clause] |
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| NavyTime (1) | | NavyTime (1) | ||
Revision as of 03:36, 11 June 2013
Data sets
Performance measures
Results
The following results refers to the TempEval-3 challenge, the last evaluation exercise.
Task A: Temporal expression extraction and normalisation
The table shows the best result for each system. Different runs per system are not shown.
| System name (best run) | Short description | Main publication | Identification | Normalisation | Overall score | Software | License | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Strict matching | Lenient matching | Accuracy | |||||||||||
| Pre. | Rec. | F1 | Pre. | Rec. | F1 | Type | Value | ||||||
| HeidelTime (t) | rule-based | Stro ̈tgen et al., 2013 | 83.85 | 78.99 | 81.34 | 93.08 | 87.68 | 90.30 | 90.91 | 85.95 | 77.61 | Download | GNU GPL v3 |
| NavyTime (1,2) | rule-based | Chambers, 2013 | 78.72 | 80.43 | 79.57 | 89.36 | 91.30 | 90.32 | 88.90 | 78.58 | 70.97 | - | - |
| ManTIME (4) | CRF, probabilistic post-processing pipeline, rule-based normaliser | Filannino et al., 2013 | 78.86 | 70.29 | 74.33 | 95.12 | 84.78 | 89.66 | 86.31 | 76.92 | 68.97 | Demo & Download | GNU GPL v2 |
| SUTime | deterministic rule-based | Chang et al., 2013 | 78.72 | 80.43 | 79.57 | 89.36 | 91.30 | 90.32 | 88.90 | 74.60 | 67.38 | Demo & Download | GNU GPL v2 |
| ATT (2) | MaxEnt, third party normalisers | Jung et al., 2013 | 90.57 | 69.57 | 78.69 | 98.11 | 75.36 | 85.25 | 91.34 | 76.91 | 65.57 | - | - |
| ClearTK (1,2) | SVM, Logistic Regression, third party normaliser | Bethard, 2013 | 85.94 | 79.71 | 82.71 | 93.75 | 86.96 | 90.23 | 93.33 | 71.66 | 64.66 | Download | BSD-3 Clause |
| JU-CSE | CRF, rule-based normaliser | Kolya et al., 2013 | 81.51 | 70.29 | 75.49 | 93.28 | 80.43 | 86.38 | 87.39 | 73.87 | 63.81 | - | - |
| KUL (2) | Logistic regression, post-processing, rule-based normaliser | Kolomiyets et al., 2013 | 76.99 | 63.04 | 69.32 | 92.92 | 76.09 | 83.67 | 88.56 | 75.24 | 62.95 | - | - |
| FSS-TimEx | rule-based | Zavarella et al., 2013 | 52.03 | 46.38 | 49.04 | 90.24 | 80.43 | 85.06 | 81.08 | 68.47 | 58.24 | - | - |
Task B: Event extraction and classification
| System name (best run) | Short description | Main publication | Identification | Attributes | Overall score | Software | License | ||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Strict matching | Accuracy | ||||||||||
| Pre. | Rec. | F1 | Class | Tense | Aspect | ||||||
| ATT (1) | Jung et al., 2013 | 81.44 | 80.67 | 81.05 | 88.69 | 73.37 | 90.68 | 71.88 | |||
| KUL (2) | Kolomiyets et al., 2013 | 80.69 | 77.99 | 79.32 | 88.46 | - | - | 70.17 | |||
| ClearTK (4) | Bethard, 2013 | 81.40 | 76.38 | 78.81 | 86.12 | 78.20 | 90.86 | 67.87 | Download | BSD-3 Clause | |
| NavyTime (1) | Chambers, 2013 | 80.73 | 79.87 | 80.30 | 84.03 | 75.79 | 91.26 | 67.48 | |||
| Temp: (ESAfeature) | X, 2013 | 78.33 | 61.61 | 68.97 | 79.09 | - | - | 54.55 | |||
| JU_CSE | Kolya et al., 2013 | 80.85 | 76.51 | 78.62 | 67.02 | 74.56 | 91.76 | 52.69 | |||
| FSS-TimeEx | Zavarella et al., 2013 | 63.13 | 67.11 | 65.06 | 66.00 | - | - | 42.94 | |||
Task C: Annotating relations given gold entities
Challenges
- TempEval, Temporal Relation Identification, 2007: web page
- TempEval-2, Evaluating Events, Time Expressions, and Temporal Relations, 2010: web page
- TempEval-3, Evaluating Time Expressions, Events, and Temporal Relations, 2013: web page
References
- UzZaman, N., Llorens, H., Derczynski, L., Allen, J., Verhagen, M., and Pustejovsky, J. Semeval-2013 task 1: Tempeval-3: Evaluating time expressions, events, and temporal relations. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 1–9.
- Bethard, S. ClearTK-TimeML: A minimalist approach to tempeval 2013. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), vol. 2, Association for Computational Linguistics, Association for Computational Linguistics, pp. 10–14.
- Stro ̈tgen, J., Zell, J., and Gertz, M. Heideltime: Tuning english and developing spanish resources for tempeval-3. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 15–19.
- Jung, H., and Stent, A. ATT1: Temporal annotation using big windows and rich syntactic and semantic features. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 20–24.
- Filannino, M., Brown, G., and Nenadic, G. ManTIME: Temporal expression identification and normalization in the Tempeval-3 challenge. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evalu- ation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 53–57.
- Zavarella, V., and Tanev, H. FSS-TimEx for tempeval-3: Extracting temporal information from text. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 58–63.
- Kolya, A. K., Kundu, A., Gupta, R., Ekbal, A., and Bandyopadhyay, S. JU_CSE: A CRF based approach to annotation of temporal expression, event and temporal relations. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 64–72.
- Chambers, N. Navytime: Event and time ordering from raw text. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 73–77.
- Chang, A., and Manning, C. D. SUTime: Evaluation in TempEval-3. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 78–82.
- Kolomiyets, O., and Moens, M.-F. KUL: Data-driven approach to temporal parsing of newswire articles. In Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceed- ings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 83–87.
- Laokulrat, N., Miwa, M., Tsuruoka, Y., and Chikayama, T. UTTime: Temporal relation classification using deep syntactic features. In Second Joint Conference on Lexical and Computational Se- mantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) (Atlanta, Georgia, USA, June 2013), Association for Computational Linguistics, pp. 88– 92.