Knowledge Base Question Answering

30 papers with code • 5 benchmarks • 8 datasets

Knowledge Base Q&A is the task of answering questions from a knowledge base.

( Image credit: Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering )

Most implemented papers

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering

dengyang17/MTQA 6 Dec 2018

Second, these two tasks can benefit each other: answer selection can incorporate the external knowledge from knowledge base (KB), while KBQA can be improved by learning contextual information from answer selection.

Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases

hugochan/BAMnet NAACL 2019

When answering natural language questions over knowledge bases (KBs), different question components and KB aspects play different roles.

KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning

INK-USC/KagNet IJCNLP 2019

Commonsense reasoning aims to empower machines with the human ability to make presumptions about ordinary situations in our daily life.

AMUSE: Multilingual Semantic Parsing for Question Answering over Linked Data

ag-sc/AMUSE 26 Feb 2018

We present the first multilingual QALD pipeline that induces a model from training data for mapping a natural language question into logical form as probabilistic inference.

Mixing Context Granularities for Improved Entity Linking on Question Answering Data across Entity Categories

UKPLab/starsem2018-entity-linking SEMEVAL 2018

We use the Wikidata knowledge base and available question answering datasets to create benchmarks for entity linking on question answering data.

Neural Machine Translation for Query Construction and Composition

LiberAI/NSpM 27 Jun 2018

Research on question answering with knowledge base has recently seen an increasing use of deep architectures.

Knowledge Base Question Answering via Encoding of Complex Query Graphs

lkq1992yeah/CompQA EMNLP 2018

Answering complex questions that involve multiple entities and multiple relations using a standard knowledge base is an open and challenging task.