200 Open source projects that are alternatives of or similar to Qa Snake

Text2Text: Cross-lingual natural language processing and generation toolkit

StarGraph (aka *graph) is a graph database to query large Knowledge Graphs. Playing with Knowledge Graphs can be useful if you are developing AI applications or doing data analysis over complex domains.

SQuAD Question Answering Using BERT, PyTorch

Participant Kit for the TextGraphs-15 Shared Task on Explanation Regeneration

Code for EMNLP-IJCNLP 2019 MRQA Workshop Paper: "Domain-agnostic Question-Answering with Adversarial Training"

API & Webapp to answer questions about COVID-19. Using NLP (Question Answering) and trusted data sources.

A question answering dataset for machine comprehension of spoken content

A deep NLP library, based on Keras / tf, focused on question answering (but useful for other NLP too)

Conversational Question Answering on Clinical Text

Portuguese translation of the SQuAD dataset

Pytorch implementation of "Dynamic Coattention Networks For Question Answering"

金融问答平台文本数据采集/爬取，数据源涉及上交所，深交所，全景网及新浪股吧

Neural network toolkit for sentence pair modeling.

DVQA Dataset: A Bar chart question answering dataset presented at CVPR 2018

⛔ [NOT MAINTAINED] An End-To-End Closed Domain Question Answering System.

Official code repository for "Exploring Neural Models for Query-Focused Summarization".

AnsPress is the most complete question and answer system for WordPress. AnsPress is made with developers in mind, highly customizable. AnsPress provide an easy to use override system for theme

Machine Comprehension Train on MSMARCO with S-NET Extraction Modification

基于自然语言理解与机器学习的聊天机器人，支持多用户并发及自定义多轮对话

Environment that can be used to evaluate reasoning capabilities of artificial agents

A question answering system for RDF knowledge graphs.

The official implementation for ACL 2021 "Challenges in Information Seeking QA: Unanswerable Questions and Paragraph Retrieval".

Source code and dataset for ACL 2019 paper "Cognitive Graph for Multi-Hop Reading Comprehension at Scale"

PororoQA, https://arxiv.org/abs/1707.00836

Multiple Meta-model Quantifying for Medical Visual Question Answering

⛔ [NOT MAINTAINED] A web interface for cdQA and other question answering systems.

Persian (Farsi) Question Answering Dataset (+ Models)

State-of-the-art natural language processing for Ruby

中文心理问答数据集

北航大数据高精尖中心研究张日崇团队对问答系统的调研。包括知识图谱问答系统（KBQA）和文本问答系统（TextQA），每类系统分别对学术界和工业界进行调研。

TensorFlow Models for the Stanford Question Answering Dataset

Fast and production-ready question answering in Node.js

Very Simple Question Answer System using Chinese Wikipedia Data

End-To-End Memory Networks for bAbI question-answering tasks

This is the official repository for NAACL 2021, "XOR QA: Cross-lingual Open-Retrieval Question Answering".

all kinds of baseline models for sentence similarity 句子对语义相似度模型

Extraction of the five journalistic W-questions (5W) from news articles

Implementation for the paper "Compositional Attention Networks for Machine Reasoning" (Hudson and Manning, ICLR 2018)

Author implementation of "Learning to Search in Long Documents Using Document Structure" (Mor Geva and Jonathan Berant, 2018)

A KBQA system based on DBpedia.

📑 Neural Search

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

Compare six baseline deep learning models on TrecQA

QA site with Python/Django

A dataset of complex questions on semi-structured Wikipedia tables

A list of recent papers about Graph Neural Network methods applied in NLP areas.

HEAD-QA: A Healthcare Dataset for Complex Reasoning

中文wiki百科QA阅读理解问答系统，使用了CCKS2016数据的NER模型和CMRC2018的阅读理解模型，还有W2V词向量搜索,使用torchserve部署

An InformationGain based Question Answering over knowledge Graph system.

Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)

Augmented version of SQUAD 2.0 for Questions

Web app that allows students to ask real-time, anonymous questions during class

[ACL 2020] DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering

ADAM - A Question Answering System. Inspired from IBM Watson

Product-Aware Answer Generation in E-Commerce Question-Answering

😎 A curated list of the Question Answering (QA)

End-to-end neural table-text understanding models.

Paper reading list in natural language processing, including dialogue systems and text generation related topics.

Extraction of the journalistic five W and one H questions (5W1H) from news articles: who did what, when, where, why, and how?

🔮 Answering multiple choice questions with Language Models.