Complex Factoid Question Answering with a Free-Text Knowledge Graph

03/23/2021
by   Chen Zhao, et al.
0

We introduce DELFT, a factoid question answering system which combines the nuance and depth of knowledge graph question answering approaches with the broader coverage of free-text. DELFT builds a free-text knowledge graph from Wikipedia, with entities as nodes and sentences in which entities co-occur as edges. For each question, DELFT finds the subgraph linking question entity nodes to candidates using text sentences as edges, creating a dense and high coverage semantic graph. A novel graph neural network reasons over the free-text graph-combining evidence on the nodes via information along edge sentences-to select a final answer. Experiments on three question answering datasets show DELFT can answer entity-rich questions better than machine reading based models, bert-based answer ranking and memory networks. DELFT's advantage comes from both the high coverage of its free-text knowledge graph-more than double that of dbpedia relations-and the novel graph neural network which reasons on the rich but noisy free-text evidence.

READ FULL TEXT

page 1

page 2

page 3

page 4

11/06/2019

Multi-Paragraph Reasoning with Knowledge-enhanced Graph Neural Network

Multi-paragraph reasoning is indispensable for open-domain question answ...
09/20/2022

Dynamic Relevance Graph Network for Knowledge-Aware Question Answering

This work investigates the challenge of learning and reasoning for Commo...
08/24/2019

Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks

In this study, we propose a novel graph neural network, called propagate...
07/13/2019

Tackling Graphical NLP problems with Graph Recurrent Networks

How to properly model graphs is a long-existing and important problem in...
10/16/2019

Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge

In this paper we present OSCAR (Ontology-based Semantic Composition Augm...
10/08/2021

KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering

Current Open-Domain Question Answering (ODQA) model paradigm often conta...
12/12/2016

Reading Comprehension using Entity-based Memory Network

This paper introduces a novel neural network model for question answerin...