Named Entity Recognition

Edit

171 papers with code · Natural Language Processing

Named entity recognition (NER) is the task of tagging entities in text with their corresponding type. Approaches typically use BIO notation, which differentiates the beginning (B) and the inside (I) of entities. O is used for non-entity tokens.

Example:

Mark	Watney	visited	Mars
B-PER	I-PER	O	B-LOC

Leaderboards

Add a Result

DATASET	BEST METHOD	PAPER TITLE	COMPARE
CoNLL 2003 (English)	CNN Large + fine-tune	Cloze-driven Pretraining of Self-attention Networks	See all
Ontonotes v5 (English)	BERT-MRC+DSC	Dice Loss for Data-imbalanced NLP Tasks	See all
ACE 2005	BERT_MRC	A Unified MRC Framework for Named Entity Recognition	See all
GENIA	BERT-MRC	A Unified MRC Framework for Named Entity Recognition	See all
JNLPBA	CollaboNet	CollaboNet: collaboration of deep neural networks for biomedical named entity recognition	See all
ACE 2004	BERT-MRC	A Unified MRC Framework for Named Entity Recognition	See all
BC5CDR	BioFLAIR	BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks	See all
SciERC	SEPT	SEPT: Improving Scientific Named Entity Recognition with Span Representation	See all
NCBI-disease	BioBERT	BioBERT: a pre-trained biomedical language representation model for biomedical text mining	See all
Long-tail emerging entities	Flair embeddings	Contextual String Embeddings for Sequence Labeling	See all
LINNAEUS	BioFLAIR	BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks	See all
Code-Switching English-Spanish NER	HME (word + BPE + char)	Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition	See all
ontontoes chinese v5	DGLSTM-CRF	Dependency-Guided LSTM-CRF for Named Entity Recognition	See all
WetLab	BiLSTM-CRF with ELMo	Using Similarity Measures to Select Pretraining Data for NER	See all
Species-800	BioFLAIR	BioFLAIR: Pretrained Pooled Contextualized Embeddings for Biomedical Sequence Labeling Tasks	See all

Subtasks

Nested Named Entity Recognition

2 leaderboards

11 papers with code

Chinese Named Entity Recognition

5 leaderboards

6 papers with code

Medical Named Entity Recognition

5 papers with code

Cross-Domain Named Entity Recognition

1 papers with code

Named Entity Recognition In Vietnamese

1 papers with code

See all 6 subtasks

Greatest papers with code

Semi-Supervised Sequence Modeling with Cross-View Training

EMNLP 2018 • tensorflow/models •

We therefore propose Cross-View Training (CVT), a semi-supervised learning algorithm that improves the representations of a Bi-LSTM sentence encoder using a mix of labeled and unlabeled data.

SOTA for CCG Supertagging on CCGBank

CCG SUPERTAGGING DEPENDENCY PARSING MACHINE TRANSLATION MULTI-TASK LEARNING NAMED ENTITY RECOGNITION UNSUPERVISED REPRESENTATION LEARNING

59,503

Paper
Code

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

NAACL 2019 • tensorflow/models •

We introduce a new language representation model called BERT, which stands for Bidirectional Encoder Representations from Transformers.

SOTA for Common Sense Reasoning on SWAG

COMMON SENSE REASONING CROSS-LINGUAL NATURAL LANGUAGE INFERENCE NAMED ENTITY RECOGNITION QUESTION ANSWERING SENTENCE CLASSIFICATION

59,500

Paper
Code

Pooled Contextualized Embeddings for Named Entity Recognition

NAACL 2019 • zalandoresearch/flair •

We make all code and pre-trained models available to the research community for use and reproduction.

#5 best model for Named Entity Recognition on CoNLL 2003 (English) (using extra training data)

NAMED ENTITY RECOGNITION

7,633

Paper
Code

Contextual String Embeddings for Sequence Labeling

COLING 2018 • zalandoresearch/flair •

Recent advances in language modeling using recurrent neural networks have made it viable to model language as distributions over characters.

SOTA for Chunking on Penn Treebank

CHUNKING LANGUAGE MODELLING NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING WORD EMBEDDINGS

7,633

Paper
Code

Deep contextualized word representations

NAACL 2018 • zalandoresearch/flair •

We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e. g., syntax and semantics), and (2) how these uses vary across linguistic contexts (i. e., to model polysemy).

#2 best model for Sentiment Analysis on SST-5 Fine-grained classification

CITATION INTENT CLASSIFICATION COREFERENCE RESOLUTION LANGUAGE MODELLING NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE QUESTION ANSWERING SEMANTIC ROLE LABELING SENTIMENT ANALYSIS

7,633

Paper
Code

Neural Architectures for Named Entity Recognition

NAACL 2016 • zalandoresearch/flair •

State-of-the-art named entity recognition systems rely heavily on hand-crafted features and domain-specific knowledge in order to learn effectively from the small, supervised training corpora that are available.

#31 best model for Named Entity Recognition on CoNLL 2003 (English)

NAMED ENTITY RECOGNITION

7,633

Paper
Code

Named Entity Recognition with Bidirectional LSTM-CNNs

TACL 2016 • zalandoresearch/flair •

Named entity recognition is a challenging task that has traditionally required large amounts of knowledge in the form of feature engineering and lexicons to achieve high performance.

ENTITY LINKING FEATURE ENGINEERING NAMED ENTITY RECOGNITION WORD EMBEDDINGS

7,633

Paper
Code