Discussion Details
| Title: | Re: A Challenge to the Minimalist Community |
| Submitter: | Emily Bender |
| Description: | I would like to respond to Carson Schütze's motor vehicle analogy,
from LL 16.1439: Consider the following analogy. You and I both are given the task of designing a motor vehicle that will get someone from point A to point B. You come back with a Corvette, I come back with an SUV. Now you say, ''Let's go to a racetrack, I'll bet I can drive a circuit faster than you, which means I have the better design.'' I will of course object: speed was not specified as the desideratum of the vehicle. Both vehicles can get a person from A to B. Moreover, the SUV can do lots of things the 'vette can't: carry more than 2 people, hold lots of luggage, play DVDs for the back seat passengers, transport moderate-sized pieces of furniture, host a small business meeting, etc. My motivation in designing it was to make it a multi-purpose family vehicle. If I were now to go back to the drafting table and modify my SUV design so that it keeps all its current features but can also go as fast as a Corvette, surely I will have achieved a much more difficult task than the person who just designed the Corvette. If I've understood the point of this analogy, it is that building a system which can take UG and some natural language input and produce a grammar which can be used to assign structures to (at least the grammatical) strings in some corpus of language is somehow outside the original point of what P&P was trying to do. I agree with Asudeh here: Even setting aside for a moment the problem of learning (i.e., the process of getting from UG to a specific language grammar), the ability to take strings and assign them structure constitutes at least part of the getting from A to B. Most P&P work (especially that within the Minimalist Program) works at a level of abstraction that seems to preclude working on the details of assigning structures to actual strings. This requires handling not only the phenomenon of interest, but its interaction with everything else required to assign structure (and meaning). Deducing that wheels and a transmisson are both required for travel from A to B is only part of the solution. Work in the theoretical frameworks that do benefit from interaction with computational linguistics (e.g., LFG, HPSG, CCG) has repeatedly shown the benefits of getting computers to keep track of all of the parts of a grammar so that the linguist can ask questions like: If I switch to this analysis of case, what other changes does that require in my grammatical system? Or, at the level of requirements on the formalism (and from the perspective of HPSG), is the simple operation of unification enough, or does an adequate account of the facts of natural language require the ability to state relational constraints? Grammatical models, when considered in all their detailed glory, are complex enough that it is not possible to reliably follow all of the implications of any proposed change in one's head or with pen and paper. The initial development of infrastructure to interpret (and parse with) grammars in any particular formalism requires an up-front investment of time. There is also time-consuming work involved in implementing theoretical ideas in order to test them. However, the benefits of both of these investments are immense. They allow us to test our ideas both for consistency with the rest of the grammatical system and against a wider range of data than is possible without computer assistance: The current fastest HPSG parser, `cheap' (developed within the PET platform of Callmeier 2000), can process a testsuite of 1000 sentences in a matter of minutes. Using the regression testing facilities of [incr tsdb()] (Oepen 2001), it is possible to compare the behavior of the current state of the grammar with earlier test runs, and look for sentences for which there are changes in predicted grammaticality, number of parses, structure of parses, etc. Furthermore, this kind of work is not restricted to monolingual investigation. As shown by the LFG ParGram (Butt et al 2002, King et al in press) and HPSG Grammar Matrix (Bender et al 2002) projects, it is possible to explore issues of universals and variation across languages in such a way that the proposed ideas can be tested by using the grammars to parse testsuites (or corpora) of the languages studied. I do not believe that all syntactic research should take place in the context of computational implementation. The implemented systems discussed above have benefitted greatly from theoretical work as well as contributing to it. At the same time, the potential benefits of computational work for theoretical inquiry should not be eschewed. References: Many of the resources mentioned above are available online at: http://www.delph-in.net Bender, Emily M., Dan Flickinger and Stephan Oepen. 2002. The Grammar Matrix: An Open-Source Starter-Kit for the Rapid Development of Cross-Linguistically Consistent Broad-Coverage Precision Grammars. In Carroll, John and Oostdijk, Nelleke and Sutcliffe, Richard (eds), Proceedings of the Workshop on Grammar Engineering and Evaluation at the 19th International Conference on Computational Linguistics. Taipei, Taiwan. pp. 8-14. Butt, Miriam, Helge Dyvik, Tracy Holloway King, H. Masuichi, and Christian Rohrer. 2002. The Parallel Grammar Project. In Carroll, John and Oostdijk, Nelleke and Sutcliffe, Richard (eds), Proceedings of the Workshop on Grammar Engineering and Evaluation at the 19th International Conference on Computational Linguistics. Taipei, Taiwan. pp. 1-7. Callmeier, Ulrich. 2000. PET --- A Platform for Experimentation with Efficient HPSG Processing Techniques. Natural Language Engineering 6 (1), Special Issue on Efficient Processing with HPSG. pp.99--108. King, Tracy Holloway, Martin Forst, Jonas Kuhn, and Miriam Butt. In press. The Feature Space in Parallel Grammar Writing. Journal of Research on Language and Computation, Special Issue on Shared Representations in Multilingual Grammar Engineering. Oepen, Stephan. 2001. [incr tsdb()] -- Competence and Performance Laboratory. User Manual. Technical Report. Computational Linguistics, Saarland University, Saarbruecken, Germany. Emily M. Bender Department of Linguistics University of Washington |
| Date Posted: | 09-May-2005 |
| Linguistic Field(s): |
Computational Linguistics
Syntax Discipline of Linguistics |
| LL Issue: | 16.1454 |
| Posted: | 09-May-2005 |
