This paper is an introduction to natural language interfaces to databases (Nlidbs). A brief overview of the history of Nlidbs is first given. Some advantages and disadvantages of Nlidbs are then discussed, comparing Nlidbs to formal query languages, form-based interfaces, and graphical interfaces. An introduction to some of the linguistic problems Nlidbs have to confront follows, for the benefit of readers less familiar with computational linguistics. The discussion then moves on to Nlidb architectures, portability issues, restricted natural language input systems (including menu-based Nlidbs), and Nlidbs with reasoning capabilities. Some less explored areas of Nlidb research are then presented, namely database updates, meta-knowledge questions, temporal questions, and multi-modal Nlidbs. The paper ends with reflections on the current state of the art. 1 Introduction A natural language interface to a database (Nlidb) is a system that allows the user to access information sto...

Masque is a powerful and portable natural language front-end for Prolog databases. It answers written English questions by generating Prolog queries, which are evaluated against the Prolog database. This paper describes a modified version of Masque, called Masque/sql, which answers English questions by generating and executing SQL code. Masque/sql maintains the full linguistic coverage of the original Masque, and can be used with any database system supporting SQL. Masque/sql is efficient, and can be easily configured using the built-in domaineditor. 2 Introduction Masque (Modular Answering System for QUeries in English) is a natural language The present paper appears in the "Proceedings of the Sixth International Conference on Industrial & Engineering Applications of Artificial Intelligence and Expert Systems", Edinburgh, 1993, proceedings published by Gordon and Breach Publishers Inc., Langhorne, PA, U.S.A. query interface for databases, developed at the Artificial Intelligen...

This article describes a method for composing fluent and complex natural language questions, while avoiding the standard pitfalls of free text queries. The method, based on Conceptual Authoring, is targeted at question-answering systems where reliability and transparency are critical, and where users cannot be expected to undergo extensive training in question composition. This scenario is found in most corporate domains, especially in applications that are risk-averse. We present a proof-of-concept system we have developed: a question-answering interface to a large repository of medical histories in the area of cancer. We show that the method allows users to successfully and reliably compose complex queries with minimal training.

This article presents the Edite system, a Natural Language Interface for Databases (NLIDB), that tries to explore the advantages of joining natural language processing with the expressiveness of graphical interfaces. In order to guarantee a permanent adaptation of this type of solution to a dynamic domain one should consider two critical fundamental factors: extensibility and portability.

A Natural Language Interface for Databases allows users of multimedia kiosks to formulate natural language questions. User questions are first translated into a logic language and subsequently into Structured Query Language (SQL), which is processed by a database management system to return the answer. This paper focuses on the translation stage. Special attention is devoted to the conceptual model, a relational database that organizes all the data supporting the translation process. The translation algorithm is presented and commented examples are used to better understand its functioning.

Natural language interfaces (NLI's) to databases allow end-users to access information in databases by typing in commands and requests in a natural language. These commands and requests are then translated into some formal database language, most commonly SQL. NLI's suffer from the same linguistic and computational problems as other natural language processing systems, though the severity of some problems is reduced due to the restricted language used and the restricted domain of discourse. Another important issue for database interfaces concerns porting them to new domains or to other natural languages. This thesis introduces a lexicalist approach to database NLI's based on unification grammars, along with a small-scale example. A sample bilingual lexicon is proposed, to demonstrate the feasibility of this approach. The solution proposed shows that a lexicalist approach is not only feasible but, for unambiguous words and expressions, can result in reasonable complexity and processing...

This paper presents a method of querying databases by means of a natural languagelike interface which offers the advantage of minimal configuration necessary for porting the system. The method allows us to first automatically infer the set of possible queries that can apply to a given database, automatically generate a lexicon and grammar rules for expressing these queries, and then provide users with an interface that allows them to pose these queries in natural language without the well-known limitations of most natural language interfaces to databases. The way the queries are inferred and constructed means that semantic translation is performed with perfect reliability.

Masque is a powerful and portable natural language front-end for Prolog databases. It answers written English questions by generating Prolog queries, whichareevaluated against the Prolog database. This paper describes a modified version of Masque, called Masque/sql,which answers English questions by generating and executing SQL code. Masque/sql maintains the full linguistic coverage of the original Masque, and can be used with any database system supporting SQL. Masque/sql is efficient, and can be easily configured using the built-in domaineditor. 2

Natural language database interfaces require translation knowledge to convert user questions into formal database queries. Previously, translation knowledge acquisition heavily depends on human specialties such as NLP, DBMS and domain engineering, consequently undermining domain portability. This paper attempts to semi-automatically construct translation knowledge by introducing a physically-derived conceptual database schema, and by simplifying translation knowledge into two structures – classreferring documents and classconstraining selection restrictions. Based on these two structures, this paper proposes a noun translation method that employs an information retrieval framework. 1