Named Entity Recognition and Extraction

This project is a named entity recognition framework and TensorFlow-based natural language processing model. It provides a pipeline for adapting pre-trained language models to specific entity recognition and text classification tasks. The system implements a sequence labeling architecture that combines transformer-based embeddings with bidirectional sequence modeling and conditional random field decoding. It includes tools for fine-tuning model weights and training the network to identify and categorize entities within unstructured text. The framework also includes a client-server architectu

Knwl.js is a JavaScript named entity recognition library and rule-based text parser. It serves as an extensible information extraction tool designed to identify and pull structured entities, such as dates, times, and locations, from unstructured text strings. The library allows for the definition of specialized rules and custom plugins to identify and extract unique pieces of information. This extensibility enables the automation of information retrieval by converting human-readable text into structured formats for applications and databases. The system utilizes regular expression matching a

CoreNLP is a Java natural language processing library designed to convert raw human language text into structured data. It utilizes a suite of linguistic annotators to analyze text through a pipeline, extracting grammatical structures, sentiment, and linguistic patterns. The project includes a coreference resolution engine that links multiple mentions of the same entity to maintain contextual consistency across documents. It also provides tools for named entity recognition to categorize people, companies, and locations, and a part-of-speech tagger to assign grammatical categories and base for

BioGPT is a biomedical large language model and domain-specific transformer designed for processing and creating specialized medical text. It functions as a generative tool and knowledge extraction engine trained on large-scale scientific literature to produce human-like scientific prose and factual responses to queries. The project provides specialized capabilities for biomedical named entity recognition and the extraction of complex relations from unstructured medical corpora. It is designed to identify and classify biological entities through data mining and relation extraction to support

This project is a tool for transforming unstructured text into semantic knowledge graphs. It uses local language models to extract entities and their relationships, converting text corpora into a structured network of linked concepts. The system provides a web interface for interactive network visualization, allowing users to navigate the resulting nodes and edges. It includes a topology analysis tool that calculates node degrees and identifies community clusters to determine the visual size and color of graph elements. Beyond visualization, the project enables graph-based information retrie

This project is a comprehensive Python toolkit designed for natural language processing, research, and education. It functions as a linguistic data processor that provides a standardized framework for managing, cleaning, and analyzing large collections of annotated text corpora and lexical resources. The library distinguishes itself through its integration of both symbolic and statistical methods, allowing users to perform complex tasks ranging from rule-based grammar parsing to machine learning-driven classification. It offers a modular pipeline for text processing, enabling the transformati

spaCy is a Python natural language processing framework designed for industrial-scale text processing. It converts raw text into structured data for machine learning pipelines through a combination of statistical language model trainers, transformer-based text processors, and syntactic dependency parsers. The project enables the integration of pretrained transformer architectures to perform complex linguistic analysis and multi-task learning. It also provides a specialized system for neural named entity recognition to identify and categorize key entities within text. The framework covers a b

Flair is a transformer-based natural language processing framework used to build and train models for text classification and sequence tagging. It provides a specialized library for generating contextual text embeddings and performing linguistic analysis. The framework includes dedicated tools for named entity recognition, including the identification of specialized biomedical entities across multiple languages. It further supports entity linking to map identified text mentions to unique entries within general or biomedical knowledge bases. The project covers a broad range of language analys

HanLP is a natural language processing library and deep learning framework specifically optimized for the Chinese language, while also functioning as a multilingual text processor. It serves as a toolkit for performing linguistic analysis, semantic understanding, and script conversion. The project distinguishes itself through a dedicated focus on Chinese linguistic structures, including a specialized script converter for transforming text between Simplified Chinese, Traditional Chinese, and Pinyin. It further supports domain-specific model training to improve the recognition of professional t

Langextract is a framework designed to transform unstructured text into structured, machine-readable data using language model orchestration. It provides a high-performance pipeline that processes large volumes of narrative text by utilizing parallel execution and sequential extraction passes. The library is built to handle complex data extraction tasks, including specialized support for clinical information and medical entity relationship recognition. The project distinguishes itself through a plugin-based architecture that supports both local hardware execution and cloud-hosted model endpoi

Flair is a natural language processing framework for training and applying models for sequence labeling and text classification. It provides a system for generating word embeddings and identifying semantic entities within text. The framework includes a dedicated system for zero and few-shot learning, enabling text classification and entity extraction using minimal training examples by leveraging pre-trained knowledge. Its capabilities cover named entity recognition, sentiment analysis, and the training of specialized models using custom datasets. It also includes tooling for the visual highl

AllenNLP is a PyTorch-based research library and deep learning language toolkit designed for developing and training neural network architectures for linguistic tasks. It provides a distributed training system that coordinates data and gradients across multiple GPUs and a framework for integrating pretrained transformer architectures. The system distinguishes itself with a dedicated algorithmic bias mitigation tool used to identify and reduce bias in linguistic model predictions. It also includes model influence analysis to interpret predictions by calculating the influence of specific traini

Entity-Relation-Extraction is a machine learning framework designed to identify entities and their logical connections within unstructured text. It functions as a pipeline that transforms raw documents into structured knowledge graphs by utilizing deep learning models and transformer architectures. The project distinguishes itself through a schema-driven approach, which maps extracted information to predefined relational templates to ensure output consistency. It employs a multi-stage process that combines sequence-labeling token classification with contextual encoding to delineate entity bou

InfoExtractor is an information extraction baseline system based on the Schema constrained Knowledge Extraction dataset(SKED). InfoExtractor adopt a pipeline architecture with a p-classification model and a so-labeling model which are both implemented with PaddlePaddle. The p-classification…

Chinese Named Entity Recognition with IDCNN/biLSTM+CRF, and Relation Extraction with biGRU+2ATT 中文实体识别与关系提取