Meaning- and ontology-based technologies for high-precision language an information-processing computational systems

Abstract

The paper addresses the need for an ontology- and meaning-based approach for natural-language-understanding and information-processing computational systems. After a discussion of an oft-ignored form/content dichotomy that offers an explicit understanding of what meaning is and is not, a specific approach, the Ontological Semantic Technology, is introduced and several aspects of meaning representation are addressed in its terms, including how the 1977 Tenerife fatal aircrash could have been prevented with its help.

Introduction

The most deadly air disaster in history is the notorious collision of KLM 4805 and Pan Am 1736 on Tenerife in 1977 ALPA n.d.. The probable cause was of a linguistic, semantic nature: the ambiguity that led to a discrepancy in grasping the state of the world between the crew of the KLM plane and air traffic control (ATC). Most egregiously, while taxiing for take-off in thick fog, a KLM crew member used the non-standard phrase, We are at take off, in communication with ATC, who responded, OK. ATC took the phrase to mean that the KLM plane had taxied to the departure point and was merely informing the tower of this fact without intending to do anything further without an ATC command. The captain of the KLM plane took the ok as his clearance to take off, which he had been waiting for impatiently, or at least not as the explicit withholding of the command to take off. The KLM plane proceeded to take off while the Pan Am plane was still taxiing on the same runway, invisible to the KLM crew because of the fog. The planes collided with only a tenth of the roughly 600 people involved surviving, all on the Pan Am plane.

Detecting, and possibly avoiding, miscommunication, in particular in potentially fatal results as in aviation radio traffic, is a motivation for the approach to automatic comprehension and disambiguation of meaning that we propose in the bulk of the paper. It is well-known that non-native speakers of English in the aviation profession, mainly air traffic control and flight crews, are a potential source of error, often fatal ones [31]. But even when English is the native language of both speakers, or one speaker when he is interacting with an instrument or computer, and even when less is at stake than in air traffic communication, differing underlying world models or differing situational instantiations of such models can result in miscommunication. Regardless of English proficiency of the human partners in the interaction, they often do not detect that a statement is compatible with two models, i.e., ambiguous. But one, sometimes both, of the models is not compatible with the actual state of the world, and if acted upon leads to deadly results. Much worse situations occur when one of the communication partners is the computer that cannot understand what a natural language text means at all. Yet, most NLP research today is not meaning-based, and neither is CAE which deals with information in natural language or, as a matter of fact, in any other form. This is precisely what the paper addresses and proposes to change, suggesting a semi-mature and partially implemented technology as a means to achieve the goal of adding the real-semantic dimension to CAE work—not to replace the current state of affairs bur rather to complement and enrich the field.