An open source library for deep learning end-to-end dialog systems and chatbots.

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.

Entity and Relation Extraction Based on TensorFlow and BERT. 基于TensorFlow和BERT的管道式实体及关系抽取，2019语言与智能技术竞赛信息抽取任务解决方案。Schema based Knowledge Extraction, SKE 2019

PyTorch solution of named entity recognition task Using Google AI's pre-trained BERT model.

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

Multiple-Relations-Extraction-Only-Look-Once. Just look at the sentence once and extract the multiple pairs of entities and their corresponding relations. 端到端联合多关系抽取模型，可用于 http://lic2019.ccf.org.cn/kg 信息抽取。

Code for http://lic2019.ccf.org.cn/kg 信息抽取。使用基于 BERT 的实体抽取和关系抽取的端到端的联合模型。

This repository contains code and datasets related to entity/knowledge papers from the VERT (Versatile Entity Recognition & disambiguation Toolkit) project, by the Knowledge Computing group at Microsoft Research Asia (MSRA).

ReFinED is an efficient and accurate entity linking (EL) system.

Open Source REST API for named entity extraction, named entity linking, named entity disambiguation, recommendation & reconciliation of entities like persons, organizations and places for (semi)automatic semantic tagging & analysis of documents by linked data knowledge graph like SKOS thesaurus, RDF ontology, database(s) or list(s) of names

使用torch整合两种经典的指针NER抽取范式，分别是SpanBert和苏神的GlobalPointer，简单加了些tricks，配置后一键运行

Fast and robust date extraction from web pages, with Python or on the command-line

Falcon 2.0 is a joint entity and relation linking tool over Wikidata.

[NAACL 2022 Findings] Good Visual Guidance Makes A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction

Automatic Entity Recognition and Typing for Domain-Specific Corpora (KDD'15)

NLP Web Service

Exploring the potential of fine-tuning Large Language Models (LLMs) like Llama2 and StableLM for medical entity extraction. This project focuses on adapting these models using PEFT, Adapter V2, and LoRA techniques to efficiently and accurately extract drug names and adverse side-effects from pharmaceutical texts

Natural language understanding library for chatbots with intent recognition and entity extraction.

Spacy pipeline object for extracting values that correspond to a named entity (e.g., birth dates, account numbers, laboratory results)

Implementing a voice enabled chatbot which converses with a user via their voice in natural language. Website: https://scalability4all.github.io/