Question Answering over BioMedical Linked Data with Grammatical Framework

نویسنده

  • Anca Marginean
چکیده

The blending of linked data with ontologies leverages the access to data. GFMed introduces grammars for a controlled natural language targeted towards biomedical linked data and the corresponding controlled SPARQL language. The grammars are described in Grammatical Framework and introduce linguistic and SPARQL phrases mostly about drugs, diseases and relationships between them. The semantic and linguistic chunks correspond to Description Logic constructors. Problems and solutions for querying biomedical linked data with Romanian, beside English, are also considered in the context of GF.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

GFMed: Question Answering over BioMedical Linked Data with Grammatical Framework

This paper reports on the participation of the system GFMed in QALD-4 question answering challenge for Biomedical interlinked data. GFMed introduces grammars for a controlled natural language targeted towards biomedical information and the corresponding controlled SPARQL language. The grammars are described in Grammatical Framework and introduce linguistic and SPARQL phrases mostly about drugs,...

متن کامل

Natural Language Question Analysis for Querying Biomedical Linked Data

Biomedical knowledge is disseminated in knowledge bases which become increasingly available on the Web. While using biomedical Linked Data is crucial, life-science researchers may have difficulties using SPARQL language. Interfaces based on Natural Language question-answering are recognised to be suitable for querying knowledge bases. In this paper, we propose a method for translating natural l...

متن کامل

Querying biomedical Linked Data with natural language questions

Recent and intensive research in the biomedical area enabled to accumulate and disseminate biomedical knowledge through various knowledge bases increasingly available on the Web. The exploitation of this knowledge requires to create links between these bases and to use them jointly. Linked Data, the SPARQL language and interfaces in natural language question answering provide interesting soluti...

متن کامل

On the SPOT: Question Answering over Temporally Enhanced Structured Data

Natural-language question answering is a convenient way for humans to discover relevant information in structured Web data such as knowledge bases or Linked Open Data sources. This paper focuses on data with a temporal dimension, and discusses the problem of mapping natural-language questions into extended SPARQL queries over RDF-structured data. We specifically address the issue of disambiguat...

متن کامل

BioASQ: A Challenge on Large-Scale Biomedical Semantic Indexing and Question Answering

This article provides an overview of BIOASQ, a new competition on biomedical semantic indexing and question answering (QA). BIOASQ aims to push towards systems that will allow biomedical workers to express their information needs in natural language and that will return concise and user-understandable answers by combining information from multiple sources of different kinds, including biomedica...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015