Results 41 to 50 of about 408,758 (354)

Concept recognition as a machine translation problem

BMC Bioinformatics, 2021
Background Automated assignment of specific ontology concepts to mentions in text is a critical task in biomedical natural language processing, and the subject of many open shared tasks.
Mayla R. Boguslav, Negacy D. Hailu, Michael Bada, William A. Baumgartner, Lawrence E. Hunter   +4 more
doaj   +1 more source

Named Entity Recognition Using Conditional Random Fields

Applied Sciences, 2022
Named entity recognition (NER) is an important task in natural language processing, as it is widely featured as a key information extraction sub-task with numerous application areas.
Wahab Khan, Ali Daud, Khurram Shahzad, Tehmina Amjad, Ameen Banjar, Heba Fasihuddin   +5 more
doaj   +1 more source

A Unified MRC Framework for Named Entity Recognition [PDF]

Annual Meeting of the Association for Computational Linguistics, 2019
The task of named entity recognition (NER) is normally divided into nested NER and flat NER depending on whether named entities are nested or not.Models are usually separately developed for the two tasks, since sequence labeling models, the most widely ...
Xiaoya Li, Jingrong Feng, Yuxian Meng, Qinghong Han, Fei Wu, Jiwei Li   +5 more
semanticscholar   +1 more source

MultiCoNER: A Large-scale Multilingual Dataset for Complex Named Entity Recognition [PDF]

International Conference on Computational Linguistics, 2022
We present AnonData, a large multilingual dataset for Named Entity Recognition that covers 3 domains (Wiki sentences, questions, and search queries) across 11 languages, as well as multilingual and code-mixing subsets.
S. Malmasi, Anjie Fang, B. Fetahu, Sudipta Kar, Oleg Rokhlenko   +4 more
semanticscholar   +1 more source

MasakhaNER: Named Entity Recognition for African Languages

Transactions of the Association for Computational Linguistics, 2021
We take a step towards addressing the under- representation of the African continent in NLP research by bringing together different stakeholders to create the first large, publicly available, high-quality dataset for named entity recognition (NER) in ten
David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, Daniel D’souza, Julia Kreutzer, Constantine Lignos, Chester Palen-Michel, Happy Buzaaba, Shruti Rijhwani, Sebastian Ruder, Stephen Mayhew, Israel Abebe Azime, Shamsuddeen H. Muhammad, Chris Chinenye Emezue, Joyce Nakatumba-Nabende, Perez Ogayo, Aremu Anuoluwapo, Catherine Gitau, Derguene Mbaye, Jesujoba Alabi, Seid Muhie Yimam, Tajuddeen Rabiu Gwadabe, Ignatius Ezeani, Rubungo Andre Niyongabo, Jonathan Mukiibi, Verrah Otiende, Iroro Orife, Davis David, Samba Ngom, Tosin Adewumi, Paul Rayson, Mofetoluwa Adeyemi, Gerald Muriuki, Emmanuel Anebi, Chiamaka Chukwuneke, Nkiruka Odu, Eric Peter Wairagala, Samuel Oyerinde, Clemencia Siro, Tobius Saul Bateesa, Temilola Oloyede, Yvonne Wambui, Victor Akinode, Deborah Nabagereka, Maurice Katusiime, Ayodele Awokoya, Mouhamadane MBOUP, Dibora Gebreyohannes, Henok Tilaye, Kelechi Nwaike, Degaga Wolde, Abdoulaye Faye, Blessing Sibanda, Orevaoghene Ahia, Bonaventure F. P. Dossou, Kelechi Ogueji, Thierno Ibrahima DIOP, Abdoulaye Diallo, Adewale Akinfaderin, Tendai Marengereke, Salomey Osei   +60 more
doaj   +1 more source

Decomposed Meta-Learning for Few-Shot Named Entity Recognition [PDF]

Findings, 2022
Few-shot named entity recognition (NER) systems aim at recognizing novel-class named entities based on only a few labeled examples. In this paper, we present a decomposed meta-learning approach which addresses the problem of few-shot NER by sequentially ...
Tingting Ma, Huiqiang Jiang, Qianhui Wu, T. Zhao, Chin-Yew Lin   +4 more
semanticscholar   +1 more source

Label Semantics for Few Shot Named Entity Recognition [PDF]

Findings, 2022
We study the problem of few shot learning for named entity recognition. Specifically, we leverage the semantic information in the names of the labels as a way of giving the model additional signal and enriched priors.
Jie Ma, Miguel Ballesteros, Srikanth Doss Kadarundalagi Raghuram Doss, Rishita Anubhai, S. Mallya, Yaser Al-Onaizan, D. Roth   +6 more
semanticscholar   +1 more source

Named entity evolution recognition on the Blogosphere [PDF]

International Journal on Digital Libraries, 2014
Advancements in technology and culture lead to changes in our language. These changes create a gap between the language known by users and the language stored in digital archives. It affects user's possibility to firstly find content and secondly interpret that content. In previous work we introduced our approach for Named Entity Evolution Recognition~(
Helge Holzmann, Nina Tahmasebi, Thomas Risse   +2 more
openaire   +2 more sources

BOND: BERT-Assisted Open-Domain Named Entity Recognition with Distant Supervision [PDF]

Knowledge Discovery and Data Mining, 2020
We study the open-domain named entity recognition (NER) problem under distant supervision. The distant supervision, though does not require large amounts of manual annotations, yields highly incomplete and noisy distant labels via external knowledge ...
Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, T. Zhao, Chao Zhang   +6 more
semanticscholar   +1 more source

Boundary Smoothing for Named Entity Recognition [PDF]

Annual Meeting of the Association for Computational Linguistics, 2022
Neural named entity recognition (NER) models may easily encounter the over-confidence issue, which degrades the performance and calibration. Inspired by label smoothing and driven by the ambiguity of boundary annotation in NER engineering, we propose ...
Enwei Zhu, Jinpeng Li
semanticscholar   +1 more source