Recent progress in leveraging deep learning methods for question answering
Question answering, serving as one of important tasks in natural language processing,
enables machines to understand questions in natural language and answer the questions …
enables machines to understand questions in natural language and answer the questions …
A Comprehensive Survey on Relation Extraction: Recent Advances and New Frontiers
Relation extraction (RE) involves identifying the relations between entities from underlying
content. RE serves as the foundation for many natural language processing (NLP) and …
content. RE serves as the foundation for many natural language processing (NLP) and …
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 …
Rng-kbqa: Generation augmented iterative ranking for knowledge base question answering
Existing KBQA approaches, despite achieving strong performance on iid test data, often
struggle in generalizing to questions involving unseen KB schema items. Prior ranking …
struggle in generalizing to questions involving unseen KB schema items. Prior ranking …
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 …
Subgraph retrieval enhanced model for multi-hop knowledge base question answering
Recent works on knowledge base question answering (KBQA) retrieve subgraphs for easier
reasoning. A desired subgraph is crucial as a small one may exclude the answer but a large …
reasoning. A desired subgraph is crucial as a small one may exclude the answer but a large …
Tiara: Multi-grained retrieval for robust question answering over large knowledge bases
Pre-trained language models (PLMs) have shown their effectiveness in multiple scenarios.
However, KBQA remains challenging, especially regarding coverage and generalization …
However, KBQA remains challenging, especially regarding coverage and generalization …
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 …