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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 1601–1625 of 1729 papers

TitleStatusHype
Synapse at CAp 2017 NER challenge: Fasttext CRF—0
Empower Sequence Labeling with Task-Aware Neural Language ModelCode0
KnowNER: Incremental Multilingual Knowledge in Named Entity Recognition—0
Bootstrapping a Romanian Corpus for Medical Named Entity Recognition—0
Role-based model for Named Entity Recognition—0
Making Travel Smarter: Extracting Travel Information From Email Itineraries Using Named Entity Recognition—0
Adapting the TTL Romanian POS Tagger to the Biomedical Domain—0
Character-based Bidirectional LSTM-CRF with words and characters for Japanese Named Entity Recognition—0
Cheap Translation for Cross-Lingual Named Entity Recognition—0
NITE: A Neural Inductive Teaching Framework for Domain Specific NER—0
NNVLP: A Neural Network-Based Vietnamese Language Processing ToolkitCode0
A neural network multi-task learning approach to biomedical named entity recognitionCode0
Unified Neural Architecture for Drug, Disease and Clinical Entity Recognition—0
RIGOTRIO at SemEval-2017 Task 9: Combining Machine Learning and Grammar Engineering for AMR Parsing and Generation—0
Joint Named Entity Recognition and Stance Detection in Tweets—0
CAp 2017 challenge: Twitter Named Entity Recognition—0
Deep Active Learning for Named Entity RecognitionCode1
Neural Reranking for Named Entity RecognitionCode0
Weakly Supervised Cross-Lingual Named Entity Recognition via Effective Annotation and Representation Projection—0
Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping—0
A Local Detection Approach for Named Entity Recognition and Mention Detection—0
Named Entity Recognition with stack residual LSTM and trainable bias decoding—0
Recognizing irregular entities in biomedical text via deep neural networks—0
Context encoders as a simple but powerful extension of word2vecCode0
Apprentissage d'agents conversationnels pour la gestion de relations clients (Training chatbots for customer relation management)—0
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