Named Entity Recognition and Linking Augmented with Large-Scale Structured Data

Paweł Rychlikowski, Bartłomiej Najdecki, Adrian Lancucki, Adam Kaczmarek


Abstract
In this paper we describe our submissions to the 2nd and 3rd SlavNER Shared Tasks held at BSNLP 2019 and BSNLP 2021, respectively. The tasks focused on the analysis of Named Entities in multilingual Web documents in Slavic languages with rich inflection. Our solution takes advantage of large collections of both unstructured and structured documents. The former serve as data for unsupervised training of language models and embeddings of lexical units. The latter refers to Wikipedia and its structured counterpart - Wikidata, our source of lemmatization rules, and real-world entities. With the aid of those resources, our system could recognize, normalize and link entities, while being trained with only small amounts of labeled data.
Anthology ID:
2021.bsnlp-1.14
Volume:
Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing
Month:
April
Year:
2021
Address:
Kiyv, Ukraine
Venue:
BSNLP
SIG:
SIGSLAV
Publisher:
Association for Computational Linguistics
Note:
Pages:
115–121
Language:
URL:
https://aclanthology.org/2021.bsnlp-1.14
DOI:
Bibkey:
Cite (ACL):
Paweł Rychlikowski, Bartłomiej Najdecki, Adrian Lancucki, and Adam Kaczmarek. 2021. Named Entity Recognition and Linking Augmented with Large-Scale Structured Data. In Proceedings of the 8th Workshop on Balto-Slavic Natural Language Processing, pages 115–121, Kiyv, Ukraine. Association for Computational Linguistics.
Cite (Informal):
Named Entity Recognition and Linking Augmented with Large-Scale Structured Data (Rychlikowski et al., BSNLP 2021)
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PDF:
https://preview.aclanthology.org/nodalida-main-page/2021.bsnlp-1.14.pdf