Named Entity Recognition on Code-Switched Data: Overview of the CALCS 2018 Shared Task

Autor:	Aguilar, Gustavo, AlGhamdi, Fahad, Soto, Victor, Diab, Mona, Hirschberg, Julia, Solorio, Thamar
Rok vydání:	2019
Předmět:	Computer Science - Computation and Language
Zdroj:	Proceedings of the Third Workshop on Computational Approaches to Linguistic Code-Switching, 2018, 138-147
Druh dokumentu:	Working Paper
Popis:	In the third shared task of the Computational Approaches to Linguistic Code-Switching (CALCS) workshop, we focus on Named Entity Recognition (NER) on code-switched social-media data. We divide the shared task into two competitions based on the English-Spanish (ENG-SPA) and Modern Standard Arabic-Egyptian (MSA-EGY) language pairs. We use Twitter data and 9 entity types to establish a new dataset for code-switched NER benchmarks. In addition to the CS phenomenon, the diversity of the entities and the social media challenges make the task considerably hard to process. As a result, the best scores of the competitions are 63.76% and 71.61% for ENG-SPA and MSA-EGY, respectively. We present the scores of 9 participants and discuss the most common challenges among submissions. Comment: ACL 2018 (CALCS)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1906.04138 Zobrazit plný text záznamu View this record from Arxiv