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.
Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering
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.
When answering natural language questions over knowledge bases (KBs), different question components and KB aspects play different roles.
Commonsense reasoning aims to empower machines with the human ability to make presumptions about ordinary situations in our daily life.
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
We use the Wikidata knowledge base and available question answering datasets to create benchmarks for entity linking on question answering data.
Answering complex questions that involve multiple entities and multiple relations using a standard knowledge base is an open and challenging task.