In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG). DBLP is an on-line reference for bibliographic information on major computer science publications that indexes over 4.4 million publications, published by more than 2.2 million authors. Our dataset consists of 10,000 question answer pairs with the corresponding SPARQL queries which can be executed over the DBLP KG to fetch the correct answer. To the best of our knowledge, this is the first QA dataset for scholarly KGs
The general goal of semantic question answering systems is to provide correct answers to natural lan...
Question Answering (QA) systems are becoming the inspiring model for the future of search engines. W...
Event-QA benchmark contains 300 semantic queries and the corresponding verbalisations for EventKG - ...
In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG). DB...
Being able to access knowledge bases in an intuitive way has been an active area of research over th...
Knowledge graphs have gained increasing popularity in the last decade in science and technology. How...
In this paper we introduce GraphDBLP, a tool that models the DBLP bibliography as a graph, and enric...
Question Answering (QA) over Knowledge Graphs (KG) has the aim of developing a system that is capabl...
Question Answering based on Knowledge Graphs (KGQA) still faces difficult challenges when transformi...
We demonstrate GraphDBLP, a tool to allow researchers for querying the DBLP bibliography as a graph....
The dataset used for this project is created by enhancing the publicly available MetaQA (Movie Text ...
Question Answering (QA) over Knowledge Graphs (KG) aims to develop a system that is capable of answe...
Answering questions on scholarly knowledge comprising text and other artifacts is a vital part of an...
Event-QA dataset contains 1000 semantic queries and the corresponding verbalisations for EventKG - a...
Question answering over knowledge graphs targets to leverage facts in knowledge graphs to answer nat...
The general goal of semantic question answering systems is to provide correct answers to natural lan...
Question Answering (QA) systems are becoming the inspiring model for the future of search engines. W...
Event-QA benchmark contains 300 semantic queries and the corresponding verbalisations for EventKG - ...
In this work we create a question answering dataset over the DBLP scholarly knowledge graph (KG). DB...
Being able to access knowledge bases in an intuitive way has been an active area of research over th...
Knowledge graphs have gained increasing popularity in the last decade in science and technology. How...
In this paper we introduce GraphDBLP, a tool that models the DBLP bibliography as a graph, and enric...
Question Answering (QA) over Knowledge Graphs (KG) has the aim of developing a system that is capabl...
Question Answering based on Knowledge Graphs (KGQA) still faces difficult challenges when transformi...
We demonstrate GraphDBLP, a tool to allow researchers for querying the DBLP bibliography as a graph....
The dataset used for this project is created by enhancing the publicly available MetaQA (Movie Text ...
Question Answering (QA) over Knowledge Graphs (KG) aims to develop a system that is capable of answe...
Answering questions on scholarly knowledge comprising text and other artifacts is a vital part of an...
Event-QA dataset contains 1000 semantic queries and the corresponding verbalisations for EventKG - a...
Question answering over knowledge graphs targets to leverage facts in knowledge graphs to answer nat...
The general goal of semantic question answering systems is to provide correct answers to natural lan...
Question Answering (QA) systems are becoming the inspiring model for the future of search engines. W...
Event-QA benchmark contains 300 semantic queries and the corresponding verbalisations for EventKG - ...