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NER

The named entity recognition (NER) involves identification of key information in the text and classification into a set of predefined categories. This includes standard entities in the text like Part of Speech (PoS) and entities like places, names etc...

Papers

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Showing 1301–1325 of 1729 papers

TitleStatusHype
Comparative Study of Zero-Shot Cross-Lingual Transfer for Bodo POS and NER Tagging Using Gemini 2.0 Flash Thinking Experimental Model—0
Comparing CNN and LSTM character-level embeddings in BiLSTM-CRF models for chemical and disease named entity recognition—0
Comparing Open Arabic Named Entity Recognition Tools—0
Comparing the Performance of NLP Toolkits and Evaluation measures in Legal Tech—0
Comparison and Adaptation of Automatic Evaluation Metrics for Quality Assessment of Re-Speaking—0
Comprehend Medical: a Named Entity Recognition and Relationship Extraction Web Service—0
Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision—0
Comprehensive Overview of Named Entity Recognition: Models, Domain-Specific Applications and Challenges—0
Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding—0
Computational Approaches to Arabic-English Code-Switching—0
Computer Science Articles Named Entity Recognition Datasets: Survey and Our Recent Development—0
CoNECo: A corpus for named entity recognition and normalization of protein complexes—0
Confidence penalty, annealing Gaussian noise and zoneout for biLSTM-CRF networks for named entity recognition—0
CoNLL#: Fine-grained Error Analysis and a Corrected Test Set for CoNLL-03 English—0
Connecting Distant Entities with Induction through Conditional Random Fields for Named Entity Recognition: Precursor-Induced CRF—0
Constructing a Knowledge Graph from Textual Descriptions of Software Vulnerabilities in the National Vulnerability Database—0
Content-Based Features to Rank Influential Hidden Services of the Tor Darknet—0
Context-aware Adversarial Training for Name Regularity Bias in Named Entity Recognition—0
Context-aware Fine-tuning of Self-supervised Speech Models—0
Contextualization and Generalization in Entity and Relation Extraction—0
Contextualized French Language Models for Biomedical Named Entity Recognition—0
Contextualized Word Representations from Distant Supervision with and for NER—0
Contextual Text Embeddings for Twi—0
ContrastNER: Contrastive-based Prompt Tuning for Few-shot NER—0
Conversion of Legal Agreements into Smart Legal Contracts using NLP—0
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