3 Stage-II: Neural Graph Search Module 对Stage-I输出的错误分析表明,实体链接的性能相当好,但关系链接的性能并非如此。因此,Stage-I生成的SPARQL中的大多数实体是正确的,但是它们之间的关系是不正确的。Stage-II中的图形搜索模块将SPARQL作为输入,并通过替换不正确的关系来生成相同的改进版本。这是一个基于bert的...
Knowledge Graph Question Answering (KGQA) is a major branch of question answering tasks, which can answer fact questions effectively by using the reasonable characteristics of the knowledge graph. Currently, lots of related works combined with a variety of deep learning models are presented for the ...
Paper:Temporal knowledge graph question answering via subgraph reasoning Github: GitHub - czy1999/SubGTR: Temporal Knowledge Graph Question Answering via Subgraph Reasoninggithub.com/czy1999/SubGTR TL;DR: 本文提出了一个基于子图推理的时序知识图谱问答(TKGQA)模型SubGTR以及一个改进的数据集Complex-Cron...
Knowledge Graph Embedding Based Question Answering 本文是论文Knowledge Graph Embedding Based Question Answering的阅读笔记和个人理解. Basic Idea 作者发现KBQA中的三个挑战问题: 谓词(
A collaboration between HTWK Leipzig, HS Anhalt, FhG IAIS and Semantic Systems @ University Hamburg - Knowledge Graph Question Answering
Add a description, image, and links to the knowledge-graph-question-answering topic page so that developers can more easily learn about it. Curate this topic Add this topic to your repo To associate your repository with the knowledge-graph-question-answering topic, visit your repo's landing...
记录下学习过NLP,就是个作业草稿 本次选取论文[1]《Knowledge Graph Embedding Based Question Answering》 论文代码网址: https://github.com/xhuang31/KEQA_WSDM19 概念介绍 Simple Question:I
知识图谱(KG)是一个多关系图,其中包含数以百万计的实体,以及连接实体的关系。知识图谱问答(Question Answering over Knowledge Graph, KGQA)是利用知识图谱信息的一项研究领域。给定一个自然语言问题和一个知识图谱,通过分析问题和 KG 中包含的信息,KGQA 系统尝试给出正确的答案。
Knowledge GraphOntology developmentGerman grammarQuestion Answering SystemQuestion Answering Systems for retrieving information from Knowledge Graphs (KG) have become a major area of interest in recent years. Current systems search for words and entities but cannot search for grammatical phenomena. The ...
知识图谱(KG)是一个多关系图,其中包含数以百万计的实体,以及连接实体的关系。知识图谱问答(Question Answering over Knowledge Graph, KGQA)是利用知识图谱信息的一项研究领域。给定一个自然语言问题和一个知识图谱,通过分析问题和 KG 中包含的信息,KGQA 系统尝试给出正确的答案。