Search Results for "entity" - Page 2
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Showing 74 open source projects for "entity"
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Frigate Home Assistant Integration
Frigate integration for Home Assistant
Frigate Home Assistant Integration connects Frigate, an AI-powered network video recorder, with Home Assistant. It allows Home Assistant users to bring Frigate camera entities, object detection events, sensors, and media access into their smart home dashboard. The integration is commonly installed through HACS, but it still requires Home Assistant configuration after installation. It depends on MQTT, because Frigate communicates many of its events and states through that channel. Users can... -
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nano-graphrag
A simple, easy-to-hack GraphRAG implementation
nano-graphrag is a lightweight implementation of the GraphRAG approach designed to simplify experimentation with graph-based retrieval-augmented generation systems. GraphRAG expands traditional RAG pipelines by constructing knowledge graphs from documents and using relationships between entities to improve the quality and reasoning of AI responses. The nano-GraphRAG project focuses on reducing complexity by providing a compact and readable codebase that preserves the core functionality of... -
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DocETL
A system for agentic LLM-powered data processing and ETL
DocETL is an open-source system designed to build and execute data processing pipelines powered by large language models, particularly for analyzing complex collections of documents and unstructured datasets. The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL... -
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Chinese-XLNet
Chinese XLNet pre-trained model
...This model is trained on large-scale Chinese text datasets to learn linguistic patterns, long-range dependencies, and semantic nuance typical of Chinese writing, making it useful for tasks like text classification, question answering, named entity recognition, and language generation. Chinese-XLNet offers an alternative to models like BERT by emphasizing autoregressive and permutation-based learning, which can lead to performance improvements on certain benchmarks and tasks. -
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LangExtract
A Python library for extracting structured information
LangExtract is a Python library developed by Google that leverages large language models (LLMs) to extract structured information from unstructured text—such as clinical notes, research papers, or literary works—based on user-defined instructions. It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and validation via automatically generated interactive HTML visualizations. LangExtract supports a wide range of models, including Google Gemini, OpenAI GPT, and local LLMs via Ollama, making it adaptable to different deployment environments and compliance needs. ... -
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Cleanlab
The standard data-centric AI package for data quality and ML
cleanlab helps you clean data and labels by automatically detecting issues in a ML dataset. To facilitate machine learning with messy, real-world data, this data-centric AI package uses your existing models to estimate dataset problems that can be fixed to train even better models. cleanlab cleans your data's labels via state-of-the-art confident learning algorithms, published in this paper and blog. See some of the datasets cleaned with cleanlab at labelerrors.com. This package helps you... -
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Controllable-RAG-Agent
This repository provides an advanced RAG
Controllable-RAG-Agent is an advanced Retrieval-Augmented Generation (RAG) system designed specifically for complex, multi-step question answering over your own documents. Instead of relying solely on simple semantic search, it builds a deterministic control graph that acts as the “brain” of the agent, orchestrating planning, retrieval, reasoning, and verification across many steps. The pipeline ingests PDFs, splits them into chapters, cleans and preprocesses text, then constructs vector... -
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Stanza
Stanford NLP Python library for many human languages
Stanza is a collection of accurate and efficient tools for the linguistic analysis of many human languages. Starting from raw text to syntactic analysis and entity recognition, Stanza brings state-of-the-art NLP models to languages of your choosing. Stanza is a Python natural language analysis package. It contains tools, which can be used in a pipeline, to convert a string containing human language text into lists of sentences and words, to generate base forms of those words, their parts of speech and morphological features, to give a syntactic structure dependency parse, and to recognize named entities. ... -
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AWS Serverless Application Model
An open-source framework for building serverless applications
The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and model it using YAML. During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Audax Data Manager
Web tool for database management
Audax Data Manager (formerly PgManage) is a modern Open-Source Database Client and Administration Tool for PostgreSQL, SQLite, Microsoft SQL Server, MySQL, MariaDB, and Oracle. Explore and edit your data, write SQL queries with smart autocomplete, monitor database performance, run background backups and more! -
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IP-XACT 2009/2014 Platform
Smart GUI/Commandline tools to create IP-XACT( 2009/2014) files
...Smart GUI to create IP-XACT Registers, Memory Maps, Address Blocks for IP- has feature to import XLS or Verilog . It has Tcl/Python API support. ipxact2verilog - Generate Verilog module from IP-XACT definition ipxact2vhdlentity - Generate VHDL entity from IP-XACT Component definition verilog2ipxact - Generates IP-XACT definition from Verilog modules vhdl2ipxact - Generates IP-XACT definition from VHDL source ipxactcoherencycheckerverilog / ipxactcoherencycheckervhdl - Validates IP-XACT Component definition with RTL validateipxact - IP-XACT Linting tool -
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Wikipedia2Vec
A tool for learning vector representations of words and entities
Wikipedia2Vec is an embedding learning tool that creates word and entity vector representations from Wikipedia, enabling NLP models to leverage structured and contextual knowledge. -
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Textinator
Internationalized highly customizable annotation and evaluation tool
Textinator is an open-source internationalized highly-customizable annotation and evaluation tool for Natural Language Processing (NLP) tasks. The tool offers a web interface with a user-friendly UI and supports a number of NLP tasks out of the box. The recommended way of deploying Textinator is through building a production version of the Docker container, as described in the Deployment guidelines. Note that the production version is most definitely more secure and reliable than the... -
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Obsei
Obsei is a low code AI powered automation tool
Obsei is an automated no-code/low-code AI-powered text observation and analysis framework, designed for extracting insights from unstructured text data such as social media, reviews, and logs. -
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InstaGraph
Converts text input or URL into knowledge graph and displays
InstaGraph is a Flask application that converts text input or a URL into a visual knowledge graph. It uses an LLM to identify entities, relationships, labels, and node types from the provided content. The generated graph is displayed visually, helping users understand relationships that may be harder to see in plain text. The project includes Graphviz-based visualization logic and supports updating an existing graph through follow-up instructions. It is designed to be simple, colorful, and... -
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Autolabel
Label, clean and enrich text datasets with LLMs
Autolabel is a Python library to label, clean and enrich datasets with Large Language Models (LLMs). Autolabel data for NLP tasks such as classification, question-answering and named entity recognition, entity matching and more. Seamlessly use commercial and open-source LLMs from providers such as OpenAI, Anthropic, HuggingFace, Google and more. -
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DeepKE
An Open Toolkit for Knowledge Graph Extraction and Construction
Supporting cnSchema, standard supervised setting, low-resource setting, document-level setting and multi-modal setting for knowledge base population. DeepKE is a knowledge extraction toolkit supporting cnSchema, standard supervised, low-resource, and document-level scenarios for entity, relation, and attribution extraction. It allows developers and researchers to customize datasets and models to extract information from unstructured texts. DeepKE supports low-resource settings with only a few labeled (e.g., 16/32 shot) instances for widespread information extraction tasks. Since relations are expressed over multiple sentences in real-world applications, DeepKE supports document-level relation extraction. ... -
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funNLP
Resources, corpora, and tools for Chinese natural language processing
...It aggregates datasets, lexicons, wordlists, sentiment dictionaries, knowledge graphs, and pretrained model references, serving as a one-stop resource hub for Chinese NLP practitioners. The repository is organized into categories such as sentiment analysis, text classification, named entity recognition, knowledge graphs, and various lexicons (e.g. sensitive words, emotion dictionaries, stopwords). It also includes links to academic papers, open-source model implementations, and practical utilities like word segmentation or text cleaning scripts. The project is highly community-oriented, frequently updated with contributions and new resources, and it’s widely used in both academic and applied NLP research. ... -
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Promptify
se GPT or other prompt based models to get structured output
...Instead of manually crafting prompts for each task, Promptify introduces a unified architecture that combines prompt templates, language model interfaces, and processing pipelines into a single framework. This approach allows developers to perform tasks such as text classification, named entity recognition, question answering, and information extraction using consistent prompt templates. The library supports integration with multiple large language model providers, enabling users to experiment with various models without changing their overall workflow. -
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sense2vec
Contextually-keyed word vectors
sense2vec (Trask et. al, 2015) is a nice twist on word2vec that lets you learn more interesting and detailed word vectors. This library is a simple Python implementation for loading, querying and training sense2vec models. For more details, check out our blog post. To explore the semantic similarities across all Reddit comments of 2015 and 2019, see the interactive demo. -
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Text Classification
All kinds of text classification models and more with deep learning
...It includes classic and advanced models such as fastText, TextCNN, BERT, TextRNN, RCNN, hierarchical attention networks, seq2seq attention, Transformers, dynamic memory networks, entity networks, ensembles, and boosting methods. The repository also includes training, prediction, testing, preprocessing, sample data, cached data guidance, and performance comparison notes. Overall, it is a hands-on reference for developers and researchers who want to experiment with deep learning methods for text classification. -
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KoNLPy
Python package for Korean natural language processing
KoNLPy is a natural language processing (NLP) library for the Korean language, offering tokenization, morphological analysis, and named entity recognition. -
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MITRE Annotation Toolkit
A toolkit for managing and manipulating text annotations
...MAT supports both UI interaction and command-line interaction, and provides various levels of control over the overall annotation process. It can be customized for specific tasks (e.g., named entity identification, de-identification of medical records). The goal of MAT is not to help you configure your training engine (in the default case, the Carafe CRF system) to achieve the best possible performance on your data. MAT is for "everything else": all the tools you end up wishing you had. -
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Kashgari
Kashgari is a production-level NLP Transfer learning framework
Kashgari is a simple and powerful NLP Transfer learning framework, build a state-of-art model in 5 minutes for named entity recognition (NER), part-of-speech tagging (PoS), and text classification tasks. -
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Chatette
A powerful dataset generator for Rasa NLU, inspired by Chatito
Chatette is a Python-based tool for generating training datasets for Natural Language Understanding (NLU) models, particularly those used with Rasa NLU. It employs a domain-specific language to define templates, enabling the creation of diverse and extensive training examples for intent classification and entity recognition.
