Results 61 to 70 of about 379,251 (377)
DAMO-NLP at SemEval-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition [PDF]
International Workshop on Semantic Evaluation, 2022 The MultiCoNER shared task aims at detecting semantically ambiguous and complex named entities in short and low-context settings for multiple languages. The lack of contexts makes the recognition of ambiguous named entities challenging. To alleviate this
Xinyu Wang +11 more
semanticscholar +1 more source
Generalisation in named entity recognition: A quantitative analysis [PDF]
Computer Speech & Language, 2017 Named Entity Recognition (NER) is a key NLP task, which is all the more challenging on Web and user-generated content with their diverse and continuously changing language. This paper aims to quantify how this diversity impacts state-of-the-art NER methods, by measuring named entity (NE) and context variability, feature sparsity, and their effects on ...
Augenstein, Isabelle +2 more
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DanfeNER - Named Entity Recognition in Nepali Tweets
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2023 Twitter allows users to easily post tweets on any subject or event anytime, generating massive amounts of rich text content on diverse topics. Automated methods such as Named Entity Recognition (NER) are required to process the massive tweet data ...
Nobal Niraula, Jeevan Chapagain
doaj +1 more source
Pattern Mining for Named Entity Recognition [PDF]
, 2014 Many evaluation campaigns have shown that knowledge-based and data-driven approaches remain equally competitive for Named Entity Recognition. Our research team has developed CasEN, a symbolic system based on finite state transducers, which achieved promising results during the Ester2 French-speaking evaluation campaign.
Nouvel, Damien +2 more
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Named Entity Recognition in Assamese [PDF]
International Journal of Computer Applications, 2016 Named Entity Recognition is a process through which a program extracts proper nouns in texts and associates them with a proper tag. NER has made significant progress in European languages, but in Indian languages due to the lack of effort as well as proper resources, it remains a challenging task.
Jugal Kalita +2 more
openaire +1 more source
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning [PDF]
Annual Meeting of the Association for Computational Linguistics, 2021 Recent advances in Named Entity Recognition (NER) show that document-level contexts can significantly improve model performance. In many application scenarios, however, such contexts are not available.
Xinyu Wang +6 more
semanticscholar +1 more source
Research Progress of Named Entity Recognition Based on Large Language Model [PDF]
Jisuanji kexue yu tansuoNamed entity recognition aims to identify named entities and their types from unstructured text, which is an important basic task in natural language processing technologies such as question answering system, machine translation and knowledge graph. With
LIANG Jia, ZHANG Liping, YAN Sheng, ZHAO Yubo, ZHANG Yawen
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AWdpCNER: Automated Wdp Chinese Named Entity Recognition from Wheat Diseases and Pests Text
Agriculture, 2023 Chinese named entity recognition of wheat diseases and pests is an initial and key step in constructing knowledge graphs. In the field of wheat diseases and pests, there are problems, such as lack of training data, nested entities, fuzzy entity ...
Demeng Zhang +4 more
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Named Entity Recognition of Wheat Diseases and Pests Fusing ALBERT and Rules [PDF]
Jisuanji kexue yu tansuo, 2023 Named entity recognition of wheat diseases and pests is a key step to building a knowledge graph. Aiming at the problems of lack of training data, complex entity structure, diverse entity types and uneven entity distribution in wheat diseases and pests ...
LIU Hebing, ZHANG Demeng, XIONG Shufeng, MA Xinming, XI Lei
doaj +1 more source
Annual Meeting of the Association for Computational Linguistics, 2020 In this paper, we study Multimodal Named Entity Recognition (MNER) for social media posts. Existing approaches for MNER mainly suffer from two drawbacks: (1) despite generating word-aware visual representations, their word representations are insensitive
Jianfei Yu, Jing Jiang, Li Yang, Rui Xia
semanticscholar +1 more source