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== References == |
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[[Category:Implicit semantic role labeling]] |
[[Category:Implicit semantic role labeling]] |
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Latest revision as of 11:05, 4 November 2018
SemEval-2010 (FrameNet)[]
SemEval-2010 (Ruppenhofer et al., 2010)[1] (Rel. = Relative, Abs. = Absolute, Over. = overlap measured by Dice coefficient)
SRL task | NI recog. | DNI vs. INI | DNI Linking | Notes | System ref | Performance ref | |||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
P | R | F1 | Rel. | Abs. | P | R | F1 | Over. | |||||
Shalmaneser | 63.32 | 38.84 | 48.12 | - | - | - | - | - | - | - | Ruppenhofer et al. (2010)[1] | ||
SEMAFOR 1.0 | 65.28 | 46.74 | 54.48 | 63.4 | 54.7 | 35 | - | - | 1.40 | - | Chen et al. (2010)[2] | Ruppenhofer et al. (2010)[1], Silberer & Frank (2012)[3] | |
CLR | 67.02 | 11.21 | 19.21 | - | - | - | - | - | - | - | Ruppenhofer et al. (2010)[1] | ||
GETARUNS++ /VENSES |
- | - | - | - 8.0 | 64.2 | 5 | - | - | 1.21 | - | Tonelli & Delmonte (2010)[4] | Ruppenhofer et al. (2010)[1], Silberer & Frank (2012)[3] | |
Silberer & Frank | - | - | - | 58 | 68 | 40 | 6.0 | 8.9 | 7.1 | - | model M0 | Silberer & Frank (2012)[3] | Silberer & Frank (2012)[3] |
Laparra & Rigau (2012) | - | - | - | - | - | - | 15 | 25 | 19 | 54 | Laparra & Rigau (2012)[5] | Laparra & Rigau (2012)[5] | |
Laparra & Rigau (2013) | - | - | - | - | - | - | 14 | 18 | 16 | 89 | Table 4 | Laparra & Rigau (2013)[6] | Laparra & Rigau (2013)[6] |
Roth & Frank (2015) | - | - | - | - | - | - | 21 | 8 | 12 | - | Table 6 (p. 650) | Roth & Frank (2015)[7] | Roth & Frank (2015)[7] |
SemEval-2010 (PropBank)[]
DNI Linking | Notes | System ref | Performance ref | ||||
---|---|---|---|---|---|---|---|
P | R | F1 | Over. | ||||
Feizabadi & Pado | 10 | 20 | 13 | - | in domain | Feizabadi & Pado (2015)[8] | Feizabadi & Pado (2015)[8] |
13 | 30 | 18 | - | SEMEVAL train + BNB | |||
Laparra and Rigau (2013) | 12 | 16 | 14 | - | - | Laparra and Rigau (2013)[6] | Feizabadi & Pado (2015)[8] |
NomBank[]
Dataset reference: Gerber and Chai (2010)[9]
Method | DNI Linking | System ref | Perform. ref | ||
---|---|---|---|---|---|
P | R | F1 | |||
Gerber & Chai | 44.5 | 40.4 | 42.3 | Gerber and Chai (2010)[9] | |
Laparra & Rigau | 47.9 | 43.8 | 45.8 | Laparra & Rigau (2012)[10] | |
Prototype vectors | 33.5 | 39.2 | 36.1 | Schenk & Chiarcos (2016)[11] | |
LSTM | 52.6 | 41.0 | 46.1 | Do et al. (2017)[12] |
References[]
- ↑ 1.0 1.1 1.2 1.3 1.4 Ruppenhofer, J., Sporleder, C., Morante, R., Baker, C., & Palmer, M. (2010). SemEval-2010 Task 10: Linking Events and Their Participants in Discourse. In Proceedings of the 5th International Workshop on Semantic Evaluation, ACL 2010 (pp. 45–50). Uppsala, Sweden.
- ↑ Chen, D., Schneider, N., Das, D., & Smith, N. A. (2010). SEMAFOR: Frame argument resolution with log-linear models. In Proceedings of the 5th International Workshop on Semantic Evaluation (pp. 264–267). Uppsala, Sweden: Association for Computational Linguistics.
- ↑ 3.0 3.1 3.2 3.3 Silberer, C., & Frank, A. (2012). Casting Implicit Role Linking As an Anaphora Resolution Task. In Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the Main Conference and the Shared Task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (pp. 1–10). Stroudsburg, PA, USA: Association for Computational Linguistics.
- ↑ Tonelli, S., & Delmonte, R. (2010). VENSES++: Adapting a deep semantic processing system to the identification of null instantiations. In Proceedings of the 5th International Workshop on Semantic Evaluations, ACL 2010 (pp. 296–299). Uppsala, Sweden: Association for Computational Linguistics.
- ↑ 5.0 5.1 Laparra, E., & Rigau, G. (2012). Exploiting Explicit Annotations and Semantic Types for Implicit Argument Resolution. In Semantic Computing (ICSC), 2012 IEEE Sixth International Conference on (pp. 75–78). doi:10.1109/ICSC.2012.47
- ↑ 6.0 6.1 6.2 Laparra, E., & Rigau, G. (2013). Sources of Evidence for Implicit Argument Resolution. In Proceedings of the 10th International Conference on Computational Semantics (IWCS2013). Potsdam, Germany.
- ↑ 7.0 7.1 Roth, M., & Frank, A. (2015). Inducing Implicit Arguments from Comparable Texts: A Framework and its Applications. Computational Linguistics, 41(4), 625–664.
- ↑ 8.0 8.1 8.2 Feizabadi, P. S., & Pado, S. (2015). Combining Seemingly Incompatible Corpora for Implicit Semantic Role Labeling. Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics (* SEM 2015 ), 40–50.
- ↑ 9.0 9.1 Matthew Gerber and Joyce Chai. 2010. Beyond Nom- Bank: A Study of Implicit Arguments for Nominal Predicates. In Proceedings of the 48th Annual Meet- ing of the Association for Computational Linguistics (ACL-2010), pages 1583–1592, Uppsala, Sweden.
- ↑ Egoitz Laparra and German Rigau. 2012. Exploiting Explicit Annotations and Semantic Types for Implicit Argument Resolution. In Proceedings of the 6th Inter- national Conference on Semantic Computing (ICSC- 2012), pages 75–78.
- ↑ Schenk, N., & Chiarcos, C. (2016). Unsupervised Learning of Prototypical Fillers for Implicit Semantic Role Labeling. In Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (pp. 1473–1479). San Diego, California: Association for Computational Linguistics.
- ↑ Do, Q. N. T., Bethard, S., & Moens, M.-F. (2017). Improving Implicit Semantic Role Labeling by Predicting Semantic Frame Arguments.