Discussion Details
| Title: | Re: A Challenge to the Minimalist Community |
| Submitter: | Peter Svenonius |
| Description: | As a theoretical linguist, I remain unconvinced from the discussion so
far that building a parser of the kind proposed by Sproat & Lappin (LINGUIST 16-1156) would be as important as they suggest. The proposal, if I understand it correctly, is to get a computer to match a corpus of e.g. newspaper texts to a set of ''hand-constructed'' trees for the sentences in that text. The allowable training procedure consists in feeding the machine pairs of sentences and trees, I gather. Unless the trees more information than is usual, it is not clear that this procedure resembles what a child does when learning a language. Recent acquisitional work stresses the importance of child-directed speech in the acquisition process, and the importance of supporting context. An important clue to the difference between ''wipe'' and ''clean'' (to take a well-studied example) is the contexts in which they're used. The meaning difference, inferrable from the contexts of use, has subtle syntactic effects that might or might not turn up in strings in a given corpus. But such contextual evidence, abundant to the learner, is necessarily ignored in the proposed scenario, because the trees don't indicate what kind of thematic relation an object has to the event it participates in. Certain aspects of intonation also turn out to be extremely important in the acquisition process, but intonation is barely indicated at all in written texts, and is underdetermined in standard trees. So the proposal seems to be to build a machine that works like another machine (i.e. the kind that Sproat & Lappin have in mind), not to build a machine that works like a human. There is a good chance that such an exercise would simply fail to advance our understanding of the human language faculty, the way the program Eliza fails to advance our understanding of human intelligence. I suppose that to make a human-like learning machine, I would first want to build a corpus that resembled the actual input to which a child typically attends, with intonation and supporting context. The input would include such information as whether a discourse referent was the same as one previously referred to or not, and whether a discourse referent appeared to be proactive or simply passive in its participation in a given event. These might be important clues for a child deciding whether something is a definite article or whether something is the syntactic subject (and these two matters might be interrelated). Then I would use that corpus as the training ground for testing my simulacrum, because P&P (Principles and Parameters) theory is not trying to describe a Language Acquisition Device that can learn a language from the Wall Street Journal (with or without labeled brackets), but a Language Acquisition Device that can learn a language from a learning environment like the one described in the preceding paragraph. If my concerns are well-founded, then building a parser of the kind described by Sproat & Lappin would not even be a milestone on the road to a workable model of language; it would be a detour. Peter Svenonius CASTL (Center for Advanced Study in Theoretical Linguistics) University of Tromsoe, Norway |
| Date Posted: | 10-May-2005 |
| Linguistic Field(s): |
Syntax
Language Acquisition |
| LL Issue: | 16.1491 |
| Posted: | 10-May-2005 |
