Named Entity Recognition (NER)

879 papers with code • 76 benchmarks • 122 datasets

Named Entity Recognition (NER) is a task of Natural Language Processing (NLP) that involves identifying and classifying named entities in a text into predefined categories such as person names, organizations, locations, and others. The goal of NER is to extract structured information from unstructured text data and represent it in a machine-readable format. 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 )

Libraries

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Latest papers with no code

LinkNER: Linking Local Named Entity Recognition Models to Large Language Models using Uncertainty

no code yet • 16 Feb 2024

Named Entity Recognition (NER) serves as a fundamental task in natural language understanding, bearing direct implications for web content analysis, search engines, and information retrieval systems.

Leveraging Large Language Models for Enhanced NLP Task Performance through Knowledge Distillation and Optimized Training Strategies

no code yet • 14 Feb 2024

Our results indicate that a strategic mix of distilled and original data markedly elevates the NER capabilities of BERT.

FaBERT: Pre-training BERT on Persian Blogs

no code yet • 9 Feb 2024

We introduce FaBERT, a Persian BERT-base model pre-trained on the HmBlogs corpus, encompassing both informal and formal Persian texts.

Named Entity Recognition for Address Extraction in Speech-to-Text Transcriptions Using Synthetic Data

no code yet • 8 Feb 2024

This paper introduces an approach for building a Named Entity Recognition (NER) model built upon a Bidirectional Encoder Representations from Transformers (BERT) architecture, specifically utilizing the SlovakBERT model.

Graph Neural Network and NER-Based Text Summarization

no code yet • 5 Feb 2024

With the abundance of data and information in todays time, it is nearly impossible for man, or, even machine, to go through all of the data line by line.

In-Context Learning for Few-Shot Nested Named Entity Recognition

no code yet • 2 Feb 2024

In nested Named entity recognition (NER), entities are nested with each other, and thus requiring more data annotations to address.

NanoNER: Named Entity Recognition for nanobiology using experts' knowledge and distant supervision

no code yet • 30 Jan 2024

It highlighted the dependency of the approach to the resource, while also confirming its ability to rediscover up to 30% of the ablated terms.

Evaluation of LLM Chatbots for OSINT-based Cyber Threat Awareness

no code yet • 26 Jan 2024

We utilize well-established data collected in previous research from Twitter to assess the competitiveness of these chatbots when compared to specialized models trained for those tasks.

Multicultural Name Recognition For Previously Unseen Names

no code yet • 23 Jan 2024

In order for downstream tasks to not exhibit bias based on cultural background, a model should perform well on names from a variety of backgrounds.

Majority or Minority: Data Imbalance Learning Method for Named Entity Recognition

no code yet • 21 Jan 2024

This imbalance leads to misclassifications of the entity classes as the O-class.