This paper describes a NL data base interface which consists oF two parts: a Natural Language Processor (NLP) and a data base application program (DBAP). The NLP is a general pur!~se language processor which builds a formal representation of the meaning of the English utterances it is given. The DBAP is an algorithm with builds a query in a augmented relational algebra from the output of the NL...

Semantic wikis support the collaborative creation, editing and utilization of semantically-enriched content, and they may therefore be well-suited to addressing problems associated with the limited availability of high-quality online semantic content. Unfortunately, however, many popular semantic wikis, such as Semantic MediaWiki (SMW), are not sufficiently expressive to support full-scale onto...

Background: Electronic Patient Records (EPRs) contain vast amounts of information in the form of texts, such as letters sent from a hospital to the patient’s local doctor (GP). The ability to extract data reliably from these texts would yield advances both in medical research and in individual patient care. In developing effective extraction methods, a crucial step is to create corpora that ali...

A Natural Language Interface for DataBase (NLIDB) is a system which accepts the user request in natural language and converts to an SQL query. The system consist of: Language Processor (LP) and Query Translator. LP is used to extract information from user query. Main LP techniques used in our system are Part-of-Speech (POS) Tagging and Chunking that are implemented by Maximum Entropy Models. Qu...

In behavioral programming, scenarios are used to program the behavior of reactive systems. Behavioral programming originated in the language of live sequence charts (LSC), a visual formalism based on multi-modal scenarios, and supported by a mechanism for directly executing a system described by a set of LSCs. In an exploratory experiment, we compare programming using LSCs with procedural progr...

Progress in natural language interfaces to databases (NLIDB) has been slow mainly due to linguistic issues (such as language ambiguity) and domain portability. Moreover, the lack of a large corpus to be used as a standard benchmark has made datadriven approaches difficult to develop and compare. In this paper, we revisit the problem of NLIDBs and recast it as a sequence translation problem. To ...

Many real-life scenarios require the joint analysis of general knowledge, which includes facts about the world, with individual knowledge, which relates to the opinions or habits of individuals. Recently developed crowd mining platforms, which were designed for such tasks, are a major step towards the solution. However, these platforms require users to specify their information needs in a forma...

Dialogue management and language processing appear as key points in virtual assistants for e-shops, as their main goal is to assist the user both in his navegation through the shop product pages and in his search for the most appropriate product. In this paper we present the details of the semantic and pragmatic approach and the dialogue management done in the ADVICE project (IST-1999-11305) fo...

Autonomous systems in remote locations have a high degree of autonomy and there is a need to explain what they are doing and why in order to increase transparency and maintain trust. Here, we describe a natural language chat interface that enables vehicle behaviour to be queried by the user. We obtain an interpretable model of autonomy through having an expert ‘speak out-loud’ and provide expla...

In this paper, we present a learning-based approach for enabling domain-awareness for a generic natural language interface. Our approach automatically acquires domain knowledge from user interactions and incorporates the knowledge learned to improve the generic system. We have embedded our approach in a generic natural language interface and evaluated the extended system against two benchmark d...