Text authoring, knowledge acquisition and description logics

Abstract

We present a principled approach to the problem of connecting a controlled document authoring system with a knowledge base. We start by describing closed-world authoring situations, in which the knowledge base is used for constraining the possible documents and orienting the user's selections. Then we move to open-world authoring situations in which, additionally, choices made during authoring are echoed back to the knowledge base. In this way the information implicitly encoded in a document becomes explicit in the knowledge base and can be re-exploited for simplifying the authoring of new documents. We show how a Datalog KB is sufficient for the closed-world situation, while a Description Logic KB is better-adapted to the more complex open-world situation. All along, we pay special attention to logically sound solutions and to decidability issues in the different processes.

A System for Ontology-Based Sharing of Expert Knowledge in Sustainability Science

“…In summary, if computer-understandable semantic statements describing expert scientific knowledge can be provided that are highly accurate and semantically rich, we could leverage advanced inference and reasoning technologies from the fields of artificial intelligence and the Semantic Web to enable computers to provide a wide range of knowledge processing services. As one example, we suggest that it should be possible to translate semantic statements created in one natural language (such as Japanese) to another (such as English), or even from one domain of knowledge (such as chemical engineering) to another (such as macroeconomics), with essentially no loss of accuracy, simply by using a relatively straightforward mapping of content models that are expressed in terms of ontologies for different knowledge domains (Bateman, 1990;Bateman et al, 2005;Dymetman, 2002;Kruijff-Korbayova & Kruijff, 1999;Kraines & Guo, 2009).…”

Using human authored description logics ABoxes as concept models for natural language generation

“…Bateman proposed the use of ontology engineering techniques and DL to create an Upper Model for “organizing domain knowledge appropriately for linguistic realization” (Bateman 1990). Several researchers have investigated the effectiveness of using different forms of DL as content models for NLG (Danlos & El Ghali 2002, Dymetman 2002, Bateman et al 2005, Kruijff‐Korbayova & Kruijff 1999). For example, Gabsdil and colleagues proposed a content model based on DL as an engine for text computer adventure games (Gabsdil et al 2001).…”

Controlled authoring of biological experiment reports

“…This difference has several decisive theoretical and practical consequences, in particular for the connection between these systems and XML-based authoring, as well as for the definability of such notions as life/death of authoring choices(Dymetman 2002). 6 http://www.xrce.xerox.com/competencies/contentanalvsis/dcm/mda.en.html 7 http://www.xrce.xerox.com/comnetencies/contentanalysis/dcm/demo/mda-demo.html…”