Proceedings of the Fifth Named Entity Workshop

doi:10.18653/v1/w15-39

2015

DOI: 10.18653/v1/w15-39

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Proceedings of the Fifth Named Entity Workshop

Abstract: The workshop series, Named Entities WorkShop (NEWS), focus on research on all aspects of the Named Entities, such as, identifying and analyzing named entities, mining, translating and transliterating named entities, etc.

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2020

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“…Gold candidate recall for four languages. translit-Wiki and translit-News refer to transliteration models trained on NEWS2015(Duan et al, 2015) and name pairs obtained from interlanguage Wikipedia links respectively. NEWS2015 does not include Oria and Sinhala.…”

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confidence: 99%

Design Challenges in Low-resource Cross-lingual Entity Linking

Fu¹,

Shi²,

Yu³

et al. 2020

Preprint

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Cross-lingual Entity Linking (XEL) grounds mentions of entities that appear in a foreign (source) language text into an English (target) knowledge base (KB) such as Wikipedia. XEL consists of two steps: candidate generation, which retrieves a list of candidate entities for each mention, followed by candidate ranking. XEL methods have been successful on high-resource languages, but generally perform poorly on low-resource languages due to lack of supervision.In this paper, we show a thorough analysis on existing low-resource XEL methods, especially on their candidate generation methods and limitations. We observed several interesting findings: 1. They are heavily limited by the Wikipedia bilingual resource coverage. 2. They perform better on Wikipedia text than on real-world text such as news or twitter. In this paper, we claim that, under the lowresource language setting, outside-Wikipedia cross-lingual resources are essential. To prove this argument, we propose a simple but effective zero-shot framework, CogCompXEL, that complements current methods by utilizing query log mapping files from online search engines. CogCompXEL outperforms current state-of-the-art models on almost all 25 languages of the LORELEI dataset, achieving an absolute average increase of 25% in gold candidate recall.

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mentioning

confidence: 99%

Design Challenges in Low-resource Cross-lingual Entity Linking

Fu¹,

Shi²,

Yu³

et al. 2020

Preprint

View full text Add to dashboard Cite

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Proceedings of the Fifth Named Entity Workshop

Abstract: The workshop series, Named Entities WorkShop (NEWS), focus on research on all aspects of the Named Entities, such as, identifying and analyzing named entities, mining, translating and transliterating named entities, etc.

Cited by 1 publication

References 45 publications

Design Challenges in Low-resource Cross-lingual Entity Linking

Design Challenges in Low-resource Cross-lingual Entity Linking

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