Results 41 to 50 of about 321,541 (313)

Bipartite Flat-Graph Network for Nested Named Entity Recognition

, 2020
In this paper, we propose a novel bipartite flat-graph network (BiFlaG) for nested named entity recognition (NER), which contains two subgraph modules: a flat NER module for outermost entities and a graph module for all the entities located in inner ...
Luo, Ying, Zhao, Hai
core   +1 more source

Pattern Mining for Named Entity Recognition [PDF]

, 2014
International audienceMany evaluation campaigns have shown that knowledge-based and data-driven approaches remain equally competitive for Named Entity Recognition.
B Bouchou, D Nadeau, DD McDonald, F Pedregosa, N Friburger, O Etzioni   +5 more
core   +3 more sources

Neural Named Entity Recognition for Kazakh

, 2023
We present several neural networks to address the task of named entity recognition for morphologically complex languages (MCL). Kazakh is a morphologically complex language in which each root/stem can produce hundreds or thousands of variant word forms.
Tolegen, Gulmira, Toleu, Alymzhan, Mamyrbayev, Orken, Mussabayev, Rustam   +3 more
openaire   +2 more sources

OWNER — Toward Unsupervised Open-World Named Entity Recognition

IEEE Access
Named Entity Recognition (NER) is a crucial task in Natural Language Processing (NLP), traditionally addressed through supervised learning, which requires extensive annotated corpora. This requirement poses challenges, particularly in specialized domains
Pierre-Yves Genest, Pierre-Edouard Portier, Elod Egyed-Zsigmond, Martino Lovisetto   +3 more
doaj   +1 more source

Named Entity recognition without gazetteers [PDF]

Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics -, 1999
It is often claimed that Named Entity recognition systems need extensive gazetteers---lists of names of people, organisations, locations, and other named entities. Indeed, the compilation of such gazetteers is sometimes mentioned as a bottleneck in the design of Named Entity recognition systems.We report on a Named Entity recognition system which ...
Andrei Mikheev, Marc Moens, Claire Grover   +2 more
openaire   +3 more sources

ChineseCTRE: A Model for Geographical Named Entity Recognition and Correction Based on Deep Neural Networks and the BERT Model

ISPRS International Journal of Geo-Information, 2023
Social media is widely used to share real-time information and report accidents during natural disasters. Named entity recognition (NER) is a fundamental task of geospatial information applications that aims to extract location names from natural ...
Wei Zhang, Jingtao Meng, Jianhua Wan, Chengkun Zhang, Jiajun Zhang, Yuanyuan Wang, Liuchang Xu, Fei Li   +7 more
doaj   +1 more source

Unsupervised Named-Entity Recognition: Generating Gazetteers and Resolving Ambiguity [PDF]

, 2006
In this paper, we propose a named-entity recognition (NER) system that addresses two major limitations frequently discussed in the field. First, the system requires no human intervention such as manually labeling training data or creating gazetteers ...
Matwin, Stan, Nadeau, David, Turney, Peter D.   +2 more
core   +2 more sources

Deep learning-based methods for natural hazard named entity recognition

Scientific Reports, 2022
Natural hazard named entity recognition is a technique used to recognize natural hazard entities from a large number of texts. The method of natural hazard named entity recognition can facilitate acquisition of natural hazards information and provide ...
Junlin Sun, Yanrong Liu, Jing Cui, Handong He   +3 more
doaj   +1 more source

HMM based Korean Named Entity Recognition [PDF]

Journal of Systemics, Cybernetics and Informatics, 2003
In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system.
Yi-Gyu Hwang, Eui-Sok Chung, Soo-jong Lim   +2 more
doaj  

Improving PARP inhibitor efficacy in bladder cancer without genetic BRCAness by combination with PLX51107

Molecular Oncology, EarlyView.
Clinical trials on PARP inhibitors in urothelial carcinoma (UC) showed limited efficacy and a lack of predictive biomarkers. We propose SLFN5, SLFN11, and OAS1 as UC‐specific response predictors. We suggest Talazoparib as the better PARP inhibitor for UC than Olaparib.
Jutta Schmitz, Anna L. Bartkowiak, Michael Rose, Nora Kolks, Patrick Petzsch, Vandana Solanki, Anne Stoffel, Bianca Faßbender, Leandra Lepping, Julka Volkamer, Karl Köhrer, Marc Seifert, Tokameh Mahmoudi, Tahlita C. M. Zuiverloon, Günter Niegisch, Michèle J. Hoffmann   +15 more
wiley   +1 more source