Browse > Natural Language Processing > Part-Of-Speech Tagging

Part-Of-Speech Tagging

75 papers with code · Natural Language Processing

Part-of-speech tagging (POS tagging) is the task of tagging a word in a text with its part of speech. A part of speech is a category of words with similar grammatical properties. Common English parts of speech are noun, verb, adjective, adverb, pronoun, preposition, conjunction, etc.

Example:

Vinken , 61 years old
NNP , CD NNS JJ

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Greatest papers with code

Globally Normalized Transition-Based Neural Networks

ACL 2016 tensorflow/models

Our model is a simple feed-forward neural network that operates on a task-specific transition system, yet achieves comparable or better accuracies than recurrent models.

DEPENDENCY PARSING PART-OF-SPEECH TAGGING SENTENCE COMPRESSION

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.

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

End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF

ACL 2016 guillaumegenthial/sequence_tagging

State-of-the-art sequence labeling systems traditionally require large amounts of task-specific knowledge in the form of hand-crafted features and data pre-processing.

FEATURE ENGINEERING NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING

Transfer Learning for Sequence Tagging with Hierarchical Recurrent Networks

18 Mar 2017jiesutd/NCRFpp

Recent papers have shown that neural networks obtain state-of-the-art performance on several different sequence tagging tasks.

FEATURE ENGINEERING NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING TRANSFER LEARNING

Chinese Lexical Analysis with Deep Bi-GRU-CRF Network

5 Jul 2018baidu/lac

Lexical analysis is believed to be a crucial step towards natural language understanding and has been widely studied.

LEXICAL ANALYSIS NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING

Empower Sequence Labeling with Task-Aware Neural Language Model

13 Sep 2017LiyuanLucasLiu/LM-LSTM-CRF

In this study, we develop a novel neural framework to extract abundant knowledge hidden in raw texts to empower the sequence labeling task.

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