Abstract
This paper introduces the Web TextFull linkage to Linked Open Data (WTF-LOD) dataset intended for large-scale evaluation of named entity recognition (NER) systems. First, we present the process of collecting data from the largest publically-available textual corpora, including Wikipedia dumps, monthly runs of the CommonCrawl, and ClueWeb09/12. We discuss similarities and differences of related initiatives such as WikiLinks and WikiReverse. Our work primarily focuses on links from “textfull” documents (links surrounded by a text that provides a useful context for entity linking), de-duplication of the data and advanced cleaning procedures. Presented statistics demonstrate that the collected data forms one of the largest available resource of its kind. They also prove suitability of the result for complex NER evaluation campaigns, including an analysis of the most ambiguous name mentions appearing in the data.- Anthology ID:
- L16-1525
- Volume:
- Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
- Month:
- May
- Year:
- 2016
- Address:
- Portorož, Slovenia
- Editors:
- Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association (ELRA)
- Note:
- Pages:
- 3299–3302
- Language:
- URL:
- https://aclanthology.org/L16-1525
- DOI:
- Cite (ACL):
- Lubomir Otrusina and Pavel Smrz. 2016. WTF-LOD - A New Resource for Large-Scale NER Evaluation. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 3299–3302, Portorož, Slovenia. European Language Resources Association (ELRA).
- Cite (Informal):
- WTF-LOD - A New Resource for Large-Scale NER Evaluation (Otrusina & Smrz, LREC 2016)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/L16-1525.pdf