Cross Lingual Named Entity Recognition using Deep Learning

Unsupervised cross-lingual model transfer for named entity ... - PLOS

Named entity recognition (NER) is one fundamental task in the natural language processing (NLP) community. Supervised neural network models ...

Analyzing transfer learning impact in biomedical cross-lingual ...

Recent NER approaches use contextualized word representations as input for a downstream classification task. However, distributed word vectors (embeddings) are ...

Cross-Lingual Named Entity Recognition for Heterogenous ...

Remarkably, when the target and source languages are heterogenous, SD-BBN can achieve a greater boost. Our results might suggest that obtaining ...

Data augmentation and transfer learning for cross-lingual Named ...

Named Entity Recognition (NER) is one of such IE tasks useful for professionals in different areas. There are several settings where biomedical ...

Enhanced Meta-Learning for Cross-Lingual Named Entity ...

For languages with no annotated resources, transferring knowledge from rich-resource languages is an effective so- lution for named entity recognition (NER).

(PDF) Cross-Lingual Named Entity Recognition Based on Attention ...

Named entity recognition aims to extract entities with specific meaning from unstructured text. Currently, deep learning methods have been ...

Multilingual Name Entity Recognition and Intent Classification ...

For the independent IC task, a Support-Vector Machine (SVM) architecture is utilized. ... The architectures we propose for this joint model are Transformer-based ...

What Is Named Entity Recognition? - IBM

The next step is to train a machine learning or deep learning model using the annotated dataset and the extracted features. The model learns to identify ...

Analyzing transfer learning impact in biomedical cross-lingual ...

These results prove that deep learning models with in-domain knowledge learned from large-scale datasets highly improve named entity ...

Reinforced Iterative Knowledge Distillation for Cross-Lingual Named ...

Instead of using training data in target languages, cross-lingual NER has to rely on only training data in source languages, and optionally adds ...

What Matters for Neural Cross-Lingual Named Entity Recognition

A simple and efficient neural architecture for cross-lingual NER that achieves competitive performance with the state-of-the-art on two transferable ...

How to perform named-entity recognition using deep learning (RNN ...

Named Entity Recognition (NER) is an NLP technique that seeks to locate and classify named entities mentioned in large unstructured text into ...

Low-Resource Named Entity Recognition via the Pre-Training Model

To learn cross-language knowledge, we used the XLM-R model, which uses a BERT architecture [24] and pre-trains on 100 languages, with a hidden layer size of 768 ...

Exploring Cross-Lingual Named Entity Recognition: A Study of the ...

These techniques are flexible and can be applied to rule-based, statistical, or machine- learning-based NER models, allowing for a comprehensive approach to ...

Cross-Lingual Transfer Learning for Named Entity Recognition in ...

This topic investigates the effectiveness of cross-lingual transfer learning for Named Entity Recognition (NER) in low-resource languages.

arXiv:1808.09861v2 [cs.CL] 11 Sep 2018

Neural Cross-Lingual Named Entity Recognition with Minimal Resources. Jiateng ... Journal of Machine Learning Research,. 12(Aug):2493–2537. Ryan ...

A Survey on Deep Learning for Named Entity Recognition - li.jing

[75] developed a multilingual NER sys- tem by using C4.5 decision tree and AdaBoostM1 learning. Page 5. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL ...

How does named entity recognition work? - Quora

Named Entity Extraction, also known as entity recognition, is a natural language processing (NLP) technique that identifies and extracts named ...

Cross-lingual Transfer Learning for Japanese Named Entity ...

This work explores cross-lingual transfer learning (TL) for named entity recognition, focusing on bootstrapping Japanese from En- glish. A deep neural ...

Deep learning for named entity recognition: a survey - OUCI

Fang Z, Cao Y, Li T, Jia R, Fang F, Shang Y, Lu Y (2021) Tebner: domain specific named entity recognition with type expanded boundary-aware network.