The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition
Open accessAbstract
This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions.Named entities form the basis of many modern approaches to other tasks (like event clustering and summarization), but recall on them is a real problem in noisy text -even among annotators.This drop tends to be due to novel entities and surface forms.Take for example the tweet "so.. kktny in 30 mins?!" -even human experts find the entity kktny hard to detect and resolve.The goal of this task is to provide a definition of emerging and of rare entities, and based on that, also datasets for detecting these entities.The task as described in this paper evaluated the ability of participating entries to detect and classify novel and emerging named entities in noisy text.
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Cites
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Chiu, J. P. C., & Nichols, E. (2016) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00104 · Cited by 1,909
Self-citationNLTK: The Natural Language Toolkit
Loper, E., & Bird, S. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0205028 · Cited by 1,844
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Sang, E. T. K. (2002) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0209010 · Cited by 1,560
Named Entity Recognition in Tweets: An Experimental Study
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Cited by
Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., & Blackburn, J. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7347 · Cited by 881
Large language models for generative information extraction: a survey
Xu, D., Chen, W., Peng, W., Zhang, C., Xu, T., Zhao, X., Wu, X., Zheng, Y., Wang, Y., & Chen, E. (2024) · Frontiers of Computer Science · doi:10.1007/s11704-024-40555-y · Cited by 326
Lai, V. D., Ngo, N. T., Veyseh, A. P. B., Man, H., Dernoncourt, F., Bui, T., & Nguyen, T. H. (2023) · arXiv · doi:10.48550/arxiv.2304.05613 · Cited by 233
Lai, V., Ngo, N., Pouran Ben Veyseh, A., Man, H., Dernoncourt, F., Bui, T., & Nguyen, T. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023 · doi:10.18653/v1/2023.findings-emnlp.878 · Cited by 233
SpanNER: Named Entity Re-/Recognition as Span Prediction
Fu, J., Huang, X., & Liu, P. (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.558 · Cited by 112
Metadata
- Authors
- Derczynski, L., Nichols, E., van Erp, M., & Limsopatham, N.
- Venue
- Proceedings of the 3rd Workshop on Noisy User-generated Text
- Published
- 2017
- Pages
- 140-147
- OpenAlex
- W2760505947
- Cited by
- 361
- References
- 33
- FWCI
- 10.04
- Type
- conference paper
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
