About

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 )

Benchmarks

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Datasets

Greatest papers with code

KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning

IJCNLP 2019 INK-USC/KagNet

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

Ranked #3 on Common Sense Reasoning on CommonsenseQA (using extra training data)

COMMON SENSE REASONING KNOWLEDGE BASE QUESTION ANSWERING KNOWLEDGE GRAPHS NATURAL LANGUAGE INFERENCE

Neural Machine Translation for Query Construction and Composition

27 Jun 2018LiberAI/NSpM

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

CODE GENERATION KNOWLEDGE BASE QUESTION ANSWERING SEMANTIC PARSING

Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases

NAACL 2019 hugochan/BAMnet

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

INFORMATION RETRIEVAL KNOWLEDGE BASE QUESTION ANSWERING SEMANTIC PARSING

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

SEMEVAL 2018 UKPLab/starsem2018-entity-linking

We investigate entity linking in the context of a question answering task and present a jointly optimized neural architecture for entity mention detection and entity disambiguation that models the surrounding context on different levels of granularity.

ENTITY DISAMBIGUATION ENTITY LINKING KNOWLEDGE BASE QUESTION ANSWERING

Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering

ACL 2019 wudapeng268/KBQA-Adapter

However, one critical problem is that current approaches only get high accuracy for questions whose relations have been seen in the training data.

KNOWLEDGE BASE QUESTION ANSWERING

Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering

16 Dec 2019siat-nlp/TransDG

In this paper, we propose a novel knowledge-aware dialogue generation model (called TransDG), which transfers question representation and knowledge matching abilities from knowledge base question answering (KBQA) task to facilitate the utterance understanding and factual knowledge selection for dialogue generation.

DIALOGUE GENERATION KNOWLEDGE BASE QUESTION ANSWERING

RuBQ: A Russian Dataset for Question Answering over Wikidata

21 May 2020vladislavneon/RuBQ

The paper presents RuBQ, the first Russian knowledge base question answering (KBQA) dataset.

ENTITY LINKING KNOWLEDGE BASE QUESTION ANSWERING