200 Open source projects that are alternatives of or similar to Denspi

Bi-directional Attention Flow (BiDAF) network is a multi-stage hierarchical process that represents context at different levels of granularity and uses a bi-directional attention flow mechanism to achieve a query-aware context representation without early summarization.

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

Reference Implementation for WSDM 2018 Paper "Hyperbolic Representation Learning for Fast and Efficient Neural Question Answering"

ADAM - A Question Answering System. Inspired from IBM Watson

Question answering over Freebase (single-relation)

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

📙 PHP 面试知识点汇总

Fast and production-ready question answering in Node.js

Русскоязычный чатбот

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

Hadamard Product for Low-rank Bilinear Pooling

A KBQA system based on DBpedia.

Entrypoint for all backend cape webservices

QA site with Python/Django

The official implementation of ACL 2020, "Logic-Guided Data Augmentation and Regularization for Consistent Question Answering".

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

Survey on Machine Reading Comprehension

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

🔎 Search the information available on a webpage using natural language instead of an exact string match.

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

My solution to the Natural Language Processing course made by Dan Jurafsky, Chris Manning in Winter 2012.

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

Code to reproduce results in our ACL 2018 paper "Did the Model Understand the Question?"

中文心理问答数据集

NLP DNN Toolkit - Building Your NLP DNN Models Like Playing Lego

TensorFlow Models for the Stanford Question Answering Dataset

A Development Center for the ZeroNet. Tutorials on ZeroNet Zite Development, Collaboration, and Questions

Very Simple Question Answer System using Chinese Wikipedia Data

🤖 Neural SPARQL Machines for Knowledge Graph Question Answering.

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

从无到有构建一个电影知识图谱，并基于该KG，开发一个简易的KBQA程序。

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

A package built on top of Hugging Face's transformer library that makes it easy to utilize state-of-the-art NLP models

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

A collection of research on knowledge graphs

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Implementation of Dynamic memory networks plus in Pytorch

Compare six baseline deep learning models on TrecQA

https://arxiv.org/abs/1707.00836

A dataset of complex questions on semi-structured Wikipedia tables

PHPer case interview questions

HEAD-QA: A Healthcare Dataset for Complex Reasoning

大规模中文自然语言处理语料 Large Scale Chinese Corpus for NLP

An InformationGain based Question Answering over knowledge Graph system.

PTT 八卦版問答中文語料

Augmented version of SQUAD 2.0 for Questions

基于多搜索引擎和深度学习技术的自动问答

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

Code for my EMNLP 2018 paper "SimpleQuestions Nearly Solved: A New Upperbound and Baseline Approach"

Persian (Farsi) Question Answering Dataset (+ Models)

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

Original implementation of QA4IE

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

Collections of Chinese reading comprehension datasets

Important paper implementations for Question Answering using PyTorch

TensorFlow implementation of Match-LSTM and Answer pointer for the popular SQuAD dataset.

Dynamic Coattention Network Plus (DCN+) TensorFlow implementation. Question answering using Deep NLP.

Datasets, SOTA results of every fields of Chinese NLP

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