CSJ Archive > Contents > Supplemental Materials > Chang:


Cognitive Science Journal | Supplemental Materials | Cognitive Science Conference Proceedings:


Chang, F. "Symbolically speaking: A connectionist model of sentence production."

The actual grammar used to generate sentences that the models were trained on deviated slightly from that reported in the article. Specifically, on benefactive datves with non-light verbs, the grammar generated sentences always without goal arguments. The following sections of the article are impacted:


pg. 612 in Table 1; pg 647, Appendix A: change "bake" to "make" in example sentences.

pg. 613: change "(e.g. make, bake)" to "(e.g. make)".

pg. 617;pg 621: remove "for the cafe" in example sentences.


pg. 638. change "only in transitive and benefactive dative frames" to "only in transitive frames."


pg. 628-629. About half of the dog-goal test items used the benefactive datives structures with DOG in the goal role. Because this meaning was associated with a two argument transitive structure (without the phrase that included the word "dog"), this test probably overestimated the ability of the models to produce this novel prepositional phrases with the word "dog". Another test set (the overt-dog-goal test set) was created made up of sentences with DOG in the goal slot, and a structure where the word "dog" was overtly produced. When tested in same manner as the original dog-goal test, the results are on the whole similar (Prod-SRN 0%, No-event-semantics model 18%, Linked-path model 36%, Dual-path model 60%). Model type is significant [F(3,9) = 12.0, p < 0.002]. Pairwise comparisons demonstrate that the Dual-path model is superior to the Prod-SRN and No-event-semantics models [Fs(1,9) > 16.3, ps < 0.003] and marginally superior to the Linked-path model [F(1,9) = 5.1, p < 0.06]. These results, in concert with the original dog-goal results, suggest that the Dual-path model is better at placing words into novel sentence positions.


None of the substantive conclusions of the study are affected by these changes.



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