Representations of commonsense knowledge: Ernest Davis

✍ Scribed by William Croft

• Publisher: Elsevier Science
• Year: 1993
• Tongue: English
• Weight: 448 KB
• Volume: 61
• Category: Article
• ISSN: 0004-3702
• DOI: 10.1016/0004-3702(93)90097-u

✦ Synopsis

Since this reviewer is a linguist, more specifically a "cognitive linguist", it is worth beginning this review with some significant differences in perspective betwecn linguistics and AI, as well as some general remarks about what each can contribute to the other.

Linguistics, in particular linguistic semantics, attempts to give an accurate and explanatory representation of the meaning of words and grammatical inflections and constructions. As such, its scope appears to be much smaller than that of knowledge representation in AI. To be sure, natural language understanding is, of course, a central concern of AI. But A1 is also concerned with perception, reasoning, planning, and other intelligent activities which appear to make little use of language. For example, planning the best route to drive to the record store can be done without uttering a word. For these reasons, knowledge representation in AI must represent a larger array of information than what appears necessary for the characterization of linguistic meaning. Also, knowledge representation is not bound to semantic distinctions and representational structures that are useful for the characterization of natural language meaning.

However, these differences are not as great as they seem. From the linguist's point of view, it is not obvious that (natural language) semantic representation is distinct from (general) knowledge representation in its scope of coverage. This is known as the "dictionary versus encyclopedia" debate in linguistics