Summary of the paper

Title Corpora for Automatically Learning to Map Natural Language Questions into SQL Queries
Authors Alessandra Giordani and Alessandro Moschitti
Abstract Automatically translating natural language into machine-readable instructions is one of major interesting and challenging tasks in Natural Language (NL) Processing. This problem can be addressed by using machine learning algorithms to generate a function that find mappings between natural language and programming language semantics. For this purpose suitable annotated and structured data are required. In this paper, we describe our method to construct and semi-automatically annotate these kinds of data, consisting of pairs of NL questions and SQL queries. Additionally, we describe two different datasets obtained by applying our annotation method to two well-known corpora, GeoQueries and RestQueries. Since we believe that syntactic levels are important, we also generate and make available relational pairs represented by means of their syntactic trees whose lexical content has been generalized. We validate the quality of our corpora by experimenting with them and our machine learning models to derive automatic NL/SQL translators. Our promising results suggest that our corpora can be effectively used to carry out research in the field of natural language interface to database.
Topics Corpus (creation, annotation, etc.), Question Answering, Knowledge Discovery/Representation
Full paper Corpora for Automatically Learning to Map Natural Language Questions into SQL Queries
Slides -
Bibtex @InProceedings{GIORDANI10.724,
  author = {Alessandra Giordani and Alessandro Moschitti},
  title = {Corpora for Automatically Learning to Map Natural Language Questions into SQL Queries},
  booktitle = {Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)},
  year = {2010},
  month = {may},
  date = {19-21},
  address = {Valletta, Malta},
  editor = {Nicoletta Calzolari (Conference Chair) and Khalid Choukri and Bente Maegaard and Joseph Mariani and Jan Odijk and Stelios Piperidis and Mike Rosner and Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-6-7},
  language = {english}
 }
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