Offline Question Answering over Linked Data using Limited Resources

eNanoMapper has been work- ing on extending the semantics of the database software to import and export data in a serialization based on the Resource Description Framework (RDF) and

Hybrid questions are provided in English and can be answered only by inte- grating structured data (RDF) and unstructured data (free text available in the DBpedia abstracts)..

To reduce the number of con- verting NL phrases to words in KB, we extract clues of answers using IRQA and generate one SPARQL based on the extracted clues and analyses of the

QAnswer is a question answering system that uses DBpe- dia as a knowledge base and converts natural language questions into a SPARQL query.. In order to improve the match

This paper presented a benchmark to train and test QA systems, composed of i) the QALM ontologies; ii) the QALM RDF dataset of product descriptions ex- tracted from eBay and

Given the following three biomedical datasets and a natural language question or set of keywords in English, the participating systems had to return either the correct answers or

Furthermore, transformation functions are valuable for a uni- form treatment of different types of resources, properties or restrictions, but they introduce on one hand (i)

We used semantic similarity based on Explicit Semantic Analysis (ESA) [13] for mapping predicates in the user NL question to predicate uniform resource identifiers