Towards portable natural language interfaces to knowledge bases – The case of the ORAKEL system

Abstract

The customization of a natural language interface to a certain application, domain or knowledge base still represents a major effort for end users given the current state-of-the-art. In this article, we present our natural language interface ORA-KEL, describe its architecture, design choices and implementation. In particular, we present ORAKEL's adaptation model which allows users which are not familiar with methods from natural language processing (NLP) or formal linguistics to port a natural language interface to a certain domain and knowledge base. The claim that our model indeed meets our requirement of intuitive adaptation is experimentally corroborated by diverse experiments with end users showing that non-NLP experts can indeed create domain lexica for our natural language interface leading to similar performance compared to lexica engineered by NLP experts.

Towards Enhanced Usability of Natural Language Interfaces to Knowledge Bases

“…However, the more technical the domain gets, the less is the chance that one can rely on lexical matching alone. In fact, it is not expected that the complete lexical knowledge necessary for very technical domains is present in general resources such as WordNet [12]. That is why domain lexicons, which contain only domain-specific vocabulary, tend to be also used by systems such as E-Librarian or ORAKEL (see Figure 3.9).…”

How Useful Are Natural Language Interfaces to the Semantic Web for Casual End-Users?

“…Considering the difficulties with full NL, it seems comprehensible that restricted NL or menuguided interfaces have been proposed by some approaches [14,22,25]. The popularity of the Semantic Web created a number of NLIs that provide access to ontology-based knowledge bases [9,11,12,15,18,26]. Most of the evaluations of NLIs mainly focus on retrieval performance and/or the portability dimension.…”

“…ORAKEL by Cimiano and colleagues [9] is a portable NLI to knowledge bases that is ontology-based in two ways. First, it uses an ontology in the inference process to answer users' queries.…”

“…-Good NLIs are often domain-or application-tailored, which makes them hardly adaptable and portable. However, if we extract the necessary information to analyse a user's NL query from a knowledge base, NLIs become domain-independent or, at least, easily adaptable to new domains [3,9]. -The retrieval performance (in terms of precision and recall) of a NLI is directly linked to the portability problem.…”

“…Several projects have shown that NLIs can perform well in retrieval tasks [12,20,24] and be portable as well as domain-independent [9,18,26] without being unnecessarily complex. This paper now attempts to shed some light on the problem dimension of usability and usefulness of NLIs (i.e., the last of the four issues raised above).…”