A collection of corpora for named entity recognition (NER) and entity recognition tasks. These annotated datasets cover a variety of languages, domains and entity types.

CCKS 2019 中文短文本实体链指比赛技术创新奖解决方案

Implementation of our papers Joint entity recognition and relation extraction as a multi-head selection problem (Expert Syst. Appl, 2018) and Adversarial training for multi-context joint entity and relation extraction (EMNLP, 2018).

Empower Sequence Labeling with Task-Aware Neural Language Model | a PyTorch Tutorial to Sequence Labeling

An overview of the AI-as-a-service landscape

Entity recognition codes for "2019 Datagrand Cup: Text Information Extraction Challenge"

Python library for custom entity recognition using Sklearn CRF

Tool to extracts the text from a web article urls and get frequency words, entities recognition, automatic summary and more

A lightweight web-based annotation tool for labelling entity recognition data.

Rust crate for entity parsing

Capsule Routing for Named Entity Recognition

The Ovation Framework for Conversational Intelligence

Software created within Accumulate project (www.accumulate.be) at CLiPS, University of Antwerp

A data labeling and NLP tool for Elixir (uses Spacy)

Musical Named Entity Recognition System for Twitter

A ERD server for 2014 Entity Recognition and Disambiguation Challenge

This project can identify names, time, and common disasters and other named entities. (本项目可以识别地名、时间和常见的灾害等命名实体。)

Flask based application to extract entities from text using Spacy.

Entity Recogniser Service for the Hu:toma Platform

A Pipeline for Entity Recognition and Relation Extraction Written in Pytorch

Extract human names from Wikipedia

A list of AI-related keywords

This is a Starter NLP Project where I have Tried to Explore Different Functionalities That Could be Achieved Using NLP Libraries, I have Used Different Libraries Such as Wikipedia, Spacy, etc to Extract the Details from a Website or more Specifically From Wikipedia and get some more Knowledge about it.

Entity recognition (organization, location, items, serial numbers) and entity normalization (organization, names) with character-level Convolutional neural network

BERT CRF model for Name Entity Recognition in pytorch

包含传统的基于统计模型(CRF)和基于深度学习(Embedding-Bi-LSTM-CRF)下的医疗数据命名实体识别

Using Microsoft Cognitive Services to demo Text Analytics powered Searching

A simple demo on how to parse empanadas flavors from sentences