Analogical hierarchy: Exemplar-based modeling of linkers in Dutch noun-noun compounds

Human Cognitive Processing

Volumn 10, Issue , 2002, Pages 181-206

  Krott, Andrea ^a   Schreuder, Robert ^a   Baayen, R Harald ^a  

^a NONE

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EID: 85190359286     PISSN: 13876724     EISSN: None     Source Type: Book Series    
DOI: 10.1075/hcp.10.14kro     Document Type: Chapter

References (33)

1. The -en- has an orthographic variant -e- which, in standard Dutch, does not differ in pronunciation.
2. We did not test any semantic rules because celex does not provide the required semantic information.
3. For a list of all applicable rules see Appendix D.
4. All results of TiMBL (version 3.0) in this paper are obtained by using the standard IB1 algorithm, the overlap similarity metric with information gain weighting, and one nearest neighbor for extrapolation. In our simulation studies, this set of parameters has been proven to lead to the best results. For AM we excluded ‘=’ as a variable, set the option ‘given’ to ‘exclude’, the option ‘probability’ to unity, and used the option ‘squared’ without specifying any frequency range.
5. Vance (1980) reports similar findings in his study of Lyman’s law which predicts the occurrence of rendaku in Japanese compounds. He concludes that rendaku is psychologically real only for a rather small minority of speakers.
6. Using different parameter settings does not enhance performance. Training on constituent, suffix, and rime while using the IGTREE algorithm leads to 30.1% correctly predicted compounds. With TRIBL we reach 37.0%. If we enhance the number of nearest neighbors for extrapolation to three, both IG and TRIBL reach a prediction accuracy of 30.1%.
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