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Named Entity Recognition

184 papers with code ยท 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

( Image credit: Zalando )

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Latest papers without code

Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning

14 Jan 2020

Word embeddings, i. e., low-dimensional vector representations such as GloVe and SGNS, encode word "meaning" in the sense that distances between words' vectors correspond to their semantic proximity.

INFORMATION RETRIEVAL LANGUAGE MODELLING NAMED ENTITY RECOGNITION TRANSFER LEARNING WORD EMBEDDINGS

A BERT based Sentiment Analysis and Key Entity Detection Approach for Online Financial Texts

14 Jan 2020

Aiming at the issue, we propose a sentiment analysis and key entity detection approach based on BERT, which is applied in online financial text mining and public opinion analysis in social media.

MACHINE READING COMPREHENSION NAMED ENTITY RECOGNITION SENTIMENT ANALYSIS

LTP: A New Active Learning Strategy for Bert-CRF Based Named Entity Recognition

8 Jan 2020

In recent years, deep learning has achieved great success in many natural language processing tasks including named entity recognition.

ACTIVE LEARNING NAMED ENTITY RECOGNITION TRANSFER LEARNING

Computationally Efficient NER Taggers with Combined Embeddings and Constrained Decoding

5 Jan 2020

The CRF layer is used to facilitate global coherence between labels, and the contextual embeddings provide a better representation of words in context.

NAMED ENTITY RECOGNITION

Towards Interpretable Evaluations: A Case Study of Named Entity Recognition

ICLR 2020

With the proliferation of models for natural language processing (NLP) tasks, it is even harder to understand the differences between models and their relative merits.

NAMED ENTITY RECOGNITION

Cross-Lingual Ability of Multilingual BERT: An Empirical Study

ICLR 2020

Recent work has exhibited the surprising cross-lingual abilities of multilingual BERT (M-BERT) -- surprising since it is trained without any cross-lingual objective and with no aligned data.

NAMED ENTITY RECOGNITION NATURAL LANGUAGE INFERENCE

Data Annealing Transfer learning Procedure for Informal Language Understanding Tasks

ICLR 2020

We propose a data annealing transfer learning procedure to bridge the performance gap on informal natural language understanding tasks.

CHUNKING NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING TRANSFER LEARNING

Semi-Supervised Named Entity Recognition with CRF-VAEs

ICLR 2020

We investigate methods for semi-supervised learning (SSL) of a neural linear-chain conditional random field (CRF) for Named Entity Recognition (NER) by treating the tagger as the amortized variational posterior in a generative model of text given tags.

NAMED ENTITY RECOGNITION

Learning to Contextually Aggregate Multi-Source Supervision for Sequence Labeling

ICLR 2020

Additionally, predictions from multiple source models in transfer learning can be seen as a case of multi-source supervision.

NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING TRANSFER LEARNING

End-to-end named entity recognition and relation extraction using pre-trained language models

ICLR 2020

In this paper, we propose a neural, end-to-end model for jointly extracting entities and their relations which does not rely on external NLP tools and which integrates a large, pre-trained language model.

LANGUAGE MODELLING NAMED ENTITY RECOGNITION RELATION EXTRACTION