Neural Generative Question Answering

12/04/2015
by   Jun Yin, et al.
HUAWEI Technologies Co., Ltd.
Peking University
0

This paper presents an end-to-end neural network model, named Neural Generative Question Answering (GENQA), that can generate answers to simple factoid questions, based on the facts in a knowledge-base. More specifically, the model is built on the encoder-decoder framework for sequence-to-sequence learning, while equipped with the ability to enquire the knowledge-base, and is trained on a corpus of question-answer pairs, with their associated triples in the knowledge-base. Empirical study shows the proposed model can effectively deal with the variations of questions and answers, and generate right and natural answers by referring to the facts in the knowledge-base. The experiment on question answering demonstrates that the proposed model can outperform an embedding-based QA model as well as a neural dialogue model trained on the same data.

READ FULL TEXT

page 1

page 2

page 3

page 4

10/09/2018

The combination of context information to enhance simple question answering

With the rapid development of knowledge base,question answering based on...
04/27/2017

Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks

Existing question answering methods infer answers either from a knowledg...
03/06/2019

Multi-Instance Learning for End-to-End Knowledge Base Question Answering

End-to-end training has been a popular approach for knowledge base quest...
11/12/2019

EDUQA: Educational Domain Question Answering System using Conceptual Network Mapping

Most of the existing question answering models can be largely compiled i...
11/07/2016

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering

We propose the Gaussian attention model for content-based neural memory ...
03/01/2019

Open Information Extraction from Question-Answer Pairs

Open Information Extraction (OpenIE) extracts meaningful structured tupl...
10/29/2020

Less is More: Data-Efficient Complex Question Answering over Knowledge Bases

Question answering is an effective method for obtaining information from...

Code Repositories

Generative_QA

Generative Question Answering


view repo

Please sign up or login with your details

Forgot password? Click here to reset