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Role-based model for Named Entity Recognition

Pablo Calleja, Raúl García-Castro, Guadalupe Aguado-de-Cea, Asunción Gómez-Pérez
2017 RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning  
Named Entity Recognition (NER) poses new challenges in real-world documents in which there are entities with different roles according to their purpose or meaning.  ...  This work proposes a NER model that relies on role classification models that support recognizing entities with a specific role.  ...  This task aims to create the role classification model based on the named entity type.  ... 
doi:10.26615/978-954-452-049-6_021 dblp:conf/ranlp/CallejaGCG17 fatcat:yofszhy4sncl5k27254yqrrjfy

Overview of Named Entity Recognition

Xing Liu, Huiqin Chen, Wangui Xia
2022 Journal of Contemporary Educational Research  
This paper discusses the existing named entity recognition technology based on its history of development.  ...  Named entity recognition, as a sub-task of information extraction, has attracted widespread attention from scholars at home and abroad since it was proposed, and a series of studies and discussions have  ...  At present, the named entity recognition technology for general texts has been established, and many researchers are focusing on the use of deep learning and attention mechanism for named entity recognition  ... 
doi:10.26689/jcer.v6i5.3958 fatcat:g4f7qga6wvd4zonfjreg4oqv64

Joint Entity and Relation Extraction Network with Enhanced Explicit and Implicit Semantic Information

Huiyan Wu, Jun Huang
2022 Applied Sciences  
Compared with the baseline model on Conll04, EINET obtains improvements by 2.37% in F1 for named entity recognition and 3.43% in F1 for relation extraction.  ...  First, on the premise of using the pre-trained model, we introduce explicit semantics from Semantic Role Labeling (SRL), which contains rich semantic features about the entity types and relation of entities  ...  Named Entity Recognition: Named Entity Recognition is mainly responsible for obtaining candidate entity representations by span-based methods.  ... 
doi:10.3390/app12126231 fatcat:676fju57xvbj3oefmxlijrdbni

A French Corpus and Annotation Schema for Named Entity Recognition and Relation Extraction of Financial News

Ali Jabbari, Olivier Sauvage, Hamada Zeine, Hamza Chergui
2020 International Conference on Language Resources and Evaluation  
The presented corpus consists of financial news articles in French and allows for training and evaluating domain-specific named entity recognition and relation extraction algorithms.  ...  We present some of our experimental results on named entity recognition and relation extraction using our annotated corpus.  ...  This ontology serves as a model for custom named entity recognition and relation extraction tasks and will eventually be used as the schema of a future knowledge base of financial relations (Jabbari et  ... 
dblp:conf/lrec/JabbariSZC20 fatcat:jmhqu2q3t5e65acypwgrbgyq7e

Poincaré Embeddings in the Task of Named Entity Recognition [chapter]

David Muñoz, Fernando Pérez, David Pinto
2020 Lecture Notes in Computer Science  
In this paper, we propose a classifier model for the NER (Named Entity Recognition) task by implementing Poincaré embeddings and by using the most frequent n-grams and their Part-of-Speech (POS) structures  ...  We found that POS structures and n-grams help to map possible named entities, while using Poincaré embeddings manage to affirm and refine this recognition, improving the recognition of named entities.  ...  In summary, this paper presents a classifier model for the task of named entity recognition by employing Poincaré embeddings, n-grams and Part-of-Speech.  ... 
doi:10.1007/978-3-030-60887-3_17 fatcat:ea7q7mcakrhd7f6gtlm2hckg5i

Large Language Models for Latvian Named Entity Recognition

Rinalds Viksna, Inguna Skadina
2020 Human Language Technology - The Baltic Perspectiv  
Transformer-based language models pre-trained on large corpora have demonstrated good results on multiple natural language processing tasks for widely used languages including named entity recognition  ...  In this paper, we investigate the role of the BERT models in the NER task for Latvian. We introduce the BERT model pre-trained on the Latvian language data.  ...  Acknowledgements This research has been supported by the European Regional Development Fund within the joint project of SIA TILDE and University of Latvia "Multilingual Artificial Intelligence Based Human  ... 
doi:10.3233/faia200603 dblp:conf/hlt/ViksnaS20 fatcat:ppejs74ihnb3njupofnzsz7vq4

Sentiment processing of social media information from both wireless and wired network

Xinzhi Wang, Hui Zhang, Shengcheng Yuan, Jiayue Wang, Yang Zhou
2016 EURASIP Journal on Wireless Communications and Networking  
During the process, name entities with the same meaning are clustered and sentiment carrier is filtered, with which sentiment can be got even users express their feeling for the same object with different  ...  Research work focuses on analyzing sentiment orientation for specific aspects of product with explicit names.  ...  At last, patterns of roles are set for person name recognition.  ... 
doi:10.1186/s13638-016-0661-x fatcat:mu2wjxmo6jg7rmzvnrwktdu63a

Automatic Recognition of Chinese Location Entity [chapter]

Xuewei Li, Xueqiang Lv, Kehui Liu
2014 Communications in Computer and Information Science  
Recognition of Chinese location entity is an important part of event extraction. In this paper we propose a novel method to identify Chinese location entity based on the divide-and-conquer strategy.  ...  Firstly, we use CRF role labeling to identify the basic place name. Secondly, by using semi-automatic way, we build indicator lexicon.  ...  Location Entity Recognition As discussed before, we use the model of location entity recognition to identify location entity. The definition of the model is as follows.  ... 
doi:10.1007/978-3-662-45924-9_34 fatcat:eimbjbpxvjfpjkni6xrnx5o2qq

NiuParser: A Chinese Syntactic and Semantic Parsing Toolkit

Jingbo Zhu, Muhua Zhu, Qiang Wang, Tong Xiao
2015 Proceedings of ACL-IJCNLP 2015 System Demonstrations  
It can handle a wide range of Natural Language Processing (NLP) tasks in Chinese, including word segmentation, partof-speech tagging, named entity recognition, chunking, constituent parsing, dependency  ...  parsing, and semantic role labeling.  ...  Named Entity Recognition In academics, named entity recognition often suffers from limited training data.  ... 
doi:10.3115/v1/p15-4025 dblp:conf/acl/ZhuZWX15 fatcat:unpery7hw5cqxjrar5rzagjk5e

Medical Named Entity Recognition Based on Overlapping Neural Networks

Ruoyu Zhang, Yuan Gao, Rui Yu, Rongyao Wang, Wenpeng Lu
2020 Procedia Computer Science  
Aiming at the existing problems, we put forward a overlapping neural network for medical named entity recognition.  ...  Aiming at the existing problems, we put forward a overlapping neural network for medical named entity recognition.  ...  For named entity recognition in the medical field, Wang et al.  ... 
doi:10.1016/j.procs.2020.06.052 fatcat:nfh7e2pxbnhzldb4u2tpy6flzu

Named Entity Recognition in Biomedical Domain: A Survey

T. M., D. Manjula, Shruthi Shridhar
2019 International Journal of Computer Applications  
Named Entity Recognition plays an important role in locating and classifying atomic elements into predefined categories such as person names, locations, organizations, expression of times, temporal expressions  ...  Named Entity Recognition (NER) is one of the major tasks in Natural Language Processing (NLP). NER has been an active area of research for the past twenty years.  ...  CONCLUSION This paper provides a review of Named Entity Recognition methods in the biomedical field.  ... 
doi:10.5120/ijca2019918469 fatcat:n2cumq3lpjgqblf64otnoxal64

Name Entity Recognition by New Framework Using Machine Learning Algorithm

Daljit Kaur, Ashish Verma
2014 IOSR Journal of Computer Engineering  
These names are called Named Entities (NE) and Named Entity Recognition (NER), one of the main tasks of IE systems, seeks to locate and classify automatically these names into predefined categories.  ...  Our approach makes use of English contextual and morphological information to extract named entities. The context is represented by means of words that are used as clues for each named entity type.  ...  about Hidden Markov Model (HMM) and the Gazetteer method for name entity recognition.  ... 
doi:10.9790/0661-16546671 fatcat:z2if4lmy6val3f7d4q6fin32s4

Product Market Demand Analysis Using NLP in Banglish Text with Sentiment Analysis and Named Entity Recognition [article]

Md Sabbir Hossain, Nishat Nayla, Annajiat Alim Rasel
2022 arXiv   pre-print
To train our datasets for named entity recognition, we utilized Spacey's custom NER model, Amazon Comprehend Custom NER.  ...  Our model has an accuracy of 87.99% in Spacy Custom Named Entity recognition, 95.51% in Amazon Comprehend Custom NER, and 87.02% in the Sequential model for demand analysis.  ...  Through the name entity recognition model we successfully identified the gender of the person based on their names.  ... 
arXiv:2204.01827v1 fatcat:u4h62fukv5b3znoqbnkcfis5x4

Recognizing Names in Islam-Related Russian Twitter

Valerie A. Mozharova, Natalia V. Loukachevitch
2017 International Conference on Data Analytics and Management in Data Intensive Domains  
Two-stage approaches to named entity recognition and Word2vec-based clustering were also useful for our task.  ...  Specific difficulties of our collection for named entity recognition include a large number of Arabic and other Eastern names and frequent use of ALL-CAPS spelling for emphasizing main words in messages  ...  The authors used two approaches for the named entity recognition: knowledge-based and CRF-based approach.  ... 
dblp:conf/rcdl/MozharovaL17 fatcat:mnvqf5la25dshggc32kyhqxbuq

Feature-Rich Twitter Named Entity Recognition and Classification

Utpal Kumar Sikdar, Björn Gambäck
2016 Workshop on Noisy User-generated Text  
For Twitter named entity recognition on unseen test data, our system obtained the second highest F 1 score in the shared task: 63.22%.  ...  Twitter named entity recognition is the process of identifying proper names and classifying them into some predefined labels/categories.  ...  Babelfy named entities: Each tweet was passed to the Babelfy (Moro et al., 2014 ) named entity recognition system for recognizing Twitter names.  ... 
dblp:conf/aclnut/SikdarG16 fatcat:cmu34hfsjvdctlsfi3latzvesm
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