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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 1351–1400 of 1729 papers

TitleStatusHype
Transfer Learning in Biomedical Named Entity Recognition: An Evaluation of BERT in the PharmaCoNER task—0
Improved Differentiable Architecture Search for Language Modeling and Named Entity RecognitionCode0
Trigger Word Detection and Thematic Role Identification via BERT and Multitask Learning—0
UCSMNLP: Statistical Machine Translation for WAT 2019—0
BIOfid Dataset: Publishing a German Gold Standard for Named Entity Recognition in Historical Biodiversity Literature—0
A Neural Pipeline Approach for the PharmaCoNER Shared Task using Contextual Exhaustive Models—0
Gazetteer-Enhanced Attentive Neural Networks for Named Entity Recognition—0
A Multi-Task Learning Framework for Extracting Bacteria Biotope Information—0
UZH@CRAFT-ST: a Sequence-labeling Approach to Concept Recognition—0
RACAI's System at PharmaCoNER 2019—0
Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph NetworkCode0
Named Entity Recognition - Is There a Glass Ceiling?—0
A Lexicon-Based Graph Neural Network for Chinese NER—0
Reinforcement-based denoising of distantly supervised NER with partial annotation—0
Contextualized Word Representations from Distant Supervision with and for NER—0
A Deep Learning-Based System for PharmaCoNER—0
Multi-Task Learning for Chemical Named Entity Recognition with Chemical Compound Paraphrasing—0
Similarity Based Auxiliary Classifier for Named Entity RecognitionCode0
A Boundary-aware Neural Model for Nested Named Entity RecognitionCode0
SoulMate: Short-text author linking through Multi-aspect temporal-textual embedding—0
A Survey on Recent Advances in Named Entity Recognition from Deep Learning modelsCode0
Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized RepresentationsCode0
Man is to Person as Woman is to Location: Measuring Gender Bias in Named Entity RecognitionCode0
Healthcare NER Models Using Language Model Pretraining—0
Comprehend Medical: a Named Entity Recognition and Relationship Extraction Web Service—0
Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy LabelsCode0
Cross-lingual Alignment vs Joint Training: A Comparative Study and A Simple Unified FrameworkCode0
Towards De-identification of Legal Texts—0
Linguistically Informed Relation Extraction and Neural Architectures for Nested Named Entity Recognition in BioNLP-OST 2019Code0
Why Attention? Analyzing and Remedying BiLSTM Deficiency in Modeling Cross-Context for NER—0
Named Entity Recognition -- Is there a glass ceiling?Code0
Content-Based Features to Rank Influential Hidden Services of the Tor Darknet—0
Distilling BERT into Simple Neural Networks with Unlabeled Transfer Data—0
Recent Advances in End-to-End Spoken Language Understanding—0
Gated Task Interaction Framework for Multi-task Sequence TaggingCode0
Language-Agnostic Syllabification with Neural Sequence LabelingCode0
Named Entity Recognition System for Sindhi Language—0
Classification Attention for Chinese NER—0
Towards Interpretable Evaluations: A Case Study of Named Entity Recognition—0
Automatic Identification and Normalisation of Physical Measurements in Scientific LiteratureCode0
Portuguese Named Entity Recognition using BERT-CRFCode0
Using Chinese Glyphs for Named Entity RecognitionCode0
Named Entity Recognition with Partially Annotated Training Data—0
Neural Correction Model for Open-Domain Named Entity RecognitionCode0
From English to Code-Switching: Transfer Learning with Strong Morphological CluesCode0
What Matters for Neural Cross-Lingual Named Entity Recognition: An Empirical Analysis—0
Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER—0
CrossWeigh: Training Named Entity Tagger from Imperfect AnnotationsCode0
All Roads Lead to UD: Converting Stanford and Penn Parses to English Universal Dependencies with Multilayer Annotations—0
Improving NER Models by exploiting Named Entity Gazetteer as External Knowledge—0
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