[HTML][HTML] Neural, symbolic and neural-symbolic reasoning on knowledge graphs
Abstract Knowledge graph reasoning is the fundamental component to support machine
learning applications such as information extraction, information retrieval, and …
learning applications such as information extraction, information retrieval, and …
A survey on complex question answering over knowledge base: Recent advances and challenges
Question Answering (QA) over Knowledge Base (KB) aims to automatically answer natural
language questions via well-structured relation information between entities stored in …
language questions via well-structured relation information between entities stored in …
Unifying large language models and knowledge graphs: A roadmap
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …
field of natural language processing and artificial intelligence, due to their emergent ability …
A survey on complex knowledge base question answering: Methods, challenges and solutions
Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Recently, a large number of studies focus on semantically or syntactically …
base (KB). Recently, a large number of studies focus on semantically or syntactically …
Query graph generation for answering multi-hop complex questions from knowledge bases
Previous work on answering complex questions from knowledge bases usually separately
addresses two types of complexity: questions with constraints and questions with multiple …
addresses two types of complexity: questions with constraints and questions with multiple …
Boosting question answering over knowledge graph with reward integration and policy evaluation under weak supervision
Among existing knowledge graph based question answering (KGQA) methods, relation
supervision methods require labeled intermediate relations for stepwise reasoning. To avoid …
supervision methods require labeled intermediate relations for stepwise reasoning. To avoid …
Lego: Latent execution-guided reasoning for multi-hop question answering on knowledge graphs
Answering complex natural language questions on knowledge graphs (KGQA) is a
challenging task. It requires reasoning with the input natural language questions as well as …
challenging task. It requires reasoning with the input natural language questions as well as …
Stepwise reasoning for multi-relation question answering over knowledge graph with weak supervision
Knowledge Graph Question Answering aims to automatically answer natural language
questions via well-structured relation information between entities stored in knowledge …
questions via well-structured relation information between entities stored in knowledge …
Complex knowledge base question answering: A survey
Knowledge base question answering (KBQA) aims to answer a question over a knowledge
base (KB). Early studies mainly focused on answering simple questions over KBs and …
base (KB). Early studies mainly focused on answering simple questions over KBs and …
SPARQA: skeleton-based semantic parsing for complex questions over knowledge bases
Semantic parsing transforms a natural language question into a formal query over a
knowledge base. Many existing methods rely on syntactic parsing like dependencies …
knowledge base. Many existing methods rely on syntactic parsing like dependencies …