Abstract
The primary goals of this tutorial are to review the framework of cross-lingual EL and motivate it as a broad paradigm for the Information Extraction task. We will start by discussing the traditional EL techniques and metrics and address questions relevant to the adequacy of these to across domains and languages. We will then present more recent approaches such as Neural EL, discuss the basic building blocks of a state-of-the-art neural EL system and analyze some of the current results on English EL. We will then proceed to Cross-lingual EL and discuss methods that work across languages. In particular, we will discuss and compare multiple methods that make use of multi-lingual word embeddings. We will also present EL methods that work for both name tagging and linking in very low resource languages. Finally, we will discuss the uses of cross-lingual EL in a variety of applications like search engines and commercial product selling applications. Also, contrary to the 2014 EL tutorial, we will also focus on Entity Discovery which is an essential component of EL.- Anthology ID:
- P18-5008
- Volume:
- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Yoav Artzi, Jacob Eisenstein
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 22–29
- Language:
- URL:
- https://aclanthology.org/P18-5008
- DOI:
- 10.18653/v1/P18-5008
- Cite (ACL):
- Avi Sil, Heng Ji, Dan Roth, and Silviu-Petru Cucerzan. 2018. Multi-lingual Entity Discovery and Linking. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, pages 22–29, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Multi-lingual Entity Discovery and Linking (Sil et al., ACL 2018)
- PDF:
- https://preview.aclanthology.org/ingest-2024-clasp/P18-5008.pdf