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Named Entity Recognition

205 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

Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models

8 Apr 2020

We propose a method for auditing the in-domain robustness of systems, focusing specifically on differences in performance due to the national origin of entities.

NAMED ENTITY RECOGNITION

Self-Attention Gazetteer Embeddings for Named-Entity Recognition

8 Apr 2020

Recent attempts to ingest external knowledge into neural models for named-entity recognition (NER) have exhibited mixed results.

NAMED ENTITY RECOGNITION

Inexpensive Domain Adaptation of Pretrained Language Models: A Case Study on Biomedical Named Entity Recognition

7 Apr 2020

Domain adaptation of Pretrained Language Models (PTLMs) is typically achieved by pretraining on in-domain text.

DOMAIN ADAPTATION NAMED ENTITY RECOGNITION

A Corpus Study and Annotation Schema for Named Entity Recognition and Relation Extraction of Business Products

LREC 2018

Recognizing non-standard entity types and relations, such as B2B products, product classes and their producers, in news and forum texts is important in application areas such as supply chain monitoring and market research.

NAMED ENTITY RECOGNITION RELATION EXTRACTION

A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events

LREC 2018

Monitoring mobility- and industry-relevant events is important in areas such as personal travel planning and supply chain management, but extracting events pertaining to specific companies, transit routes and locations from heterogeneous, high-volume text streams remains a significant challenge.

NAMED ENTITY RECOGNITION RELATION EXTRACTION

The Russian Drug Reaction Corpus and Neural Models for Drug Reactions and Effectiveness Detection in User Reviews

7 Apr 2020

For the sentence classification task, our model achieves the macro F1 score of 68. 82% gaining 7. 47% over the score of BERT model trained on Russian data.

NAMED ENTITY RECOGNITION SENTENCE CLASSIFICATION

Deep Learning Approach for Intelligent Named Entity Recognition of Cyber Security

31 Mar 2020

In recent years, the amount of Cyber Security data generated in the form of unstructured texts, for example, social media resources, blogs, articles, and so on has exceptionally increased.

NAMED ENTITY RECOGNITION

Named Entities in Medical Case Reports: Corpus and Experiments

29 Mar 2020

We present a new corpus comprising annotations of medical entities in case reports, originating from PubMed Central's open access library.

NAMED ENTITY RECOGNITION RELATION EXTRACTION

Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision

27 Mar 2020

We created this CORD-19-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus (2020- 03-13).

NAMED ENTITY RECOGNITION

E2EET: From Pipeline to End-to-end Entity Typing via Transformer-Based Embeddings

23 Mar 2020

They are therefore sensitive to window size selection and are unable to incorporate the context of the entire document.

ENTITY TYPING NAMED ENTITY RECOGNITION