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Named Entity Recognition

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TitleStatusHype
Vancouver Welcomes You! Minimalist Location Metonymy ResolutionCode0
Bayesian Modeling of Lexical Resources for Low-Resource Settings—0
A Local Detection Approach for Named Entity Recognition and Mention Detection—0
Recurrent neural networks with specialized word embeddings for health-domain named-entity recognitionCode0
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
Exploration de traits pour la reconnaissance d'entit\'es nomm\'ees du Fran par apprentissage automatique (Feature exploration for French Named Entity Recognition with Machine Learning)—0
Morphological Embeddings for Named Entity Recognition in Morphologically Rich Languages—0
The Importance of Automatic Syntactic Features in Vietnamese Named Entity Recognition—0
Second-Order Word Embeddings from Nearest Neighbor Topological FeaturesCode0
Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML—0
Transfer Learning for Named-Entity Recognition with Neural Networks—0
NeuroNER: an easy-to-use program for named-entity recognition based on neural networksCode0
End-to-end Recurrent Neural Network Models for Vietnamese Named Entity Recognition: Word-level vs. Character-levelCode0
Entity Linking with people entity on Wikipedia—0
The Effect of Excluding Out of Domain Training Data from Supervised Named-Entity Recognition—0
Semi-supervised sequence tagging with bidirectional language modelsCode0
Semi-supervised Multitask Learning for Sequence LabelingCode1
Differentiable Scheduled Sampling for Credit Assignment—0
SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data—0
Language-Independent Named Entity Analysis Using Parallel Projection and Rule-Based Disambiguation—0
The First Cross-Lingual Challenge on Recognition, Normalization, and Matching of Named Entities in Slavic Languages—0
Liner2 --- a Generic Framework for Named Entity Recognition—0
Toward Pan-Slavic NLP: Some Experiments with Language Adaptation—0
TWINE: A real-time system for TWeet analysis via INformation Extraction—0
Efficient Benchmarking of NLP APIs using Multi-armed Bandits—0
Probabilistic Inference for Cold Start Knowledge Base Population with Prior World Knowledge—0
Named Entity Recognition in the Medical Domain with Constrained CRF Models—0
A Tidy Data Model for Natural Language Processing using cleanNLPCode0
Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers—0
Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised FeaturesCode0
Decoding with Finite-State Transducers on GPUs—0
Generalisation in Named Entity Recognition: A Quantitative Analysis—0
Graph Convolutional Networks for Named Entity RecognitionCode0
Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling—0
PAMPO: using pattern matching and pos-tagging for effective Named Entities recognition in PortugueseCode0
Sparse Coding of Neural Word Embeddings for Multilingual Sequence Labeling—0
A natural language interface to a graph-based bibliographic information retrieval system—0
Mongolian Named Entity Recognition System with Rich Features—0
Named Entity Recognition for Linguistic Rapid Response in Low-Resource Languages: Sorani Kurdish and Tajik—0
Broad Twitter Corpus: A Diverse Named Entity Recognition Resource—0
CharNER: Character-Level Named Entity RecognitionCode0
Bitext Name Tagging for Cross-lingual Entity Annotation Projection—0
PersoNER: Persian Named-Entity RecognitionCode0
Illinois Cross-Lingual Wikifier: Grounding Entities in Many Languages to the English Wikipedia—0
Entity-Supported Summarization of Biomedical Abstracts—0
Named Entity Recognition in Swedish Health Records with Character-Based Deep Bidirectional LSTMsCode0
Learning Orthographic Features in Bi-directional LSTM for Biomedical Named Entity Recognition—0
Analyzing Impact, Trend, and Diffusion of Knowledge associated with Neoplasms Research—0
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