Comparing two trainable grammatical relations finders

Details Comparing two trainable grammatical relations finders Comparing two trainable grammatical relations finders

2000-08-08

arxiv.org/abs/cs/0008004v1

18th International Conference on Computational Linguistics (COLING 2000), pages 1146-1150, Saarbruecken, Germany, July, 2000

Computer Science

Computation and Language

5 pages, uses colacl.sty

Scientific paper

Grammatical relationships (GRs) form an important level of natural language processing, but different sets of GRs are useful for different purposes. Therefore, one may often only have time to obtain a small training corpus with the desired GR annotations. On such a small training corpus, we compare two systems. They use different learning techniques, but we find that this difference by itself only has a minor effect. A larger factor is that in English, a different GR length measure appears better suited for finding simple argument GRs than for finding modifier GRs. We also find that partitioning the data may help memory-based learning.

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