Query Formulation from High-Level Concepts for Relational Databases
UIDIS '99 Proceedings of the 1999 User Interfaces to Data Intensive Systems
Using semantic templates for a natural language interface to the CINDI virtual library
Data & Knowledge Engineering - Special issue: Natural language and database and information systems: NLDB 03
Proceedings of the 12th international conference on Intelligent user interfaces
Towards Building Robust Natural Language Interfaces to Databases
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Generic querying of relational databases using natural language generation techniques
INLG '06 Proceedings of the Fourth International Natural Language Generation Conference
Dialogue manager for a NLIDB for solving the semantic ellipsis problem in query formulation
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
A domain independent natural language interface to databases capable of processing complex queries
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Semantic mapping between natural language questions and SQL queries via syntactic pairing
NLDB'09 Proceedings of the 14th international conference on Applications of Natural Language to Information Systems
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Despite the fact that since the late 60s many Natural Language Interfaces to Databases (NLIDBs) have been developed, up to now many problems continue, which prevent the translation process from natural language to SQL to be totally successful. Some of the main problems that have been encountered relate to 1) achieving domain independence, 2) the use of words or phrases of different syntactic categories for referring to tables and columns, and 3) semantic ellipsis. This paper introduces a new method for modeling databases that includes relevant information for improving the performance of NLIDBs. This method will be useful for solving many problems found in the translation from natural language to SQL, using a database model that contains linguistic information that provides more semantic information than that found in conventional database models (such as the extended entity-relationship model) and those used in previous NLIDBs.