WebQSP
Related Papers
Improved Neural Relation Detection for Knowledge Base Question Answering
AbstractRelation detection is a core component of many NLP applications including Knowledge Base Question Answering (KBQA). In this paper, we propose a hierarchical recurrent neural network enhanced by residual learning …...
Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader
AbstractWe propose a new end-to-end question answering model, which learns to aggregate answer evidence from an incomplete knowledge base (KB) and a set of retrieved text snippets. Under the assumptions …...
UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answering
AbstractIn relation extraction for knowledge-based question answering, searching from one entity to another entity via a single relation is called “one hop”. In related work, an exhaustive search from all …...
Efficient One-Pass End-to-End Entity Linking for Questions
AbstractWe present ELQ, a fast end-to-end entity linking model for questions, which uses a biencoder to jointly perform mention detection and linking in one pass. Evaluated on WebQSP and GraphQuestions …...
Large-Scale Relation Learning for Question Answering over Knowledge Bases with Pre-trained Language Models
AbstractThe key challenge of question answering over knowledge bases (KBQA) is the inconsistency between the natural language questions and the reasoning paths in the knowledge base (KB). Recent graph-based KBQA …...
A Sequential Flow Control Framework for Multi-hop Knowledge Base Question Answering
AbstractOne of the key challenges of knowledge base question answering (KBQA) is the multi-hop reasoning. Since in different hops, one attends to different parts of question, it is important to …...
RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering
AbstractExisting KBQA approaches, despite achieving strong performance on i.i.d. test data, often struggle in generalizing to questions involving unseen KB schema items. Prior ranking-based approaches have shown some success in …...
Few-shot In-context Learning on Knowledge Base Question Answering
AbstractQuestion answering over knowledge bases is considered a difficult problem due to the challenge of generalizing to a wide variety of possible natural language questions. Additionally, the heterogeneity of knowledge …...