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Modelling function words improves unsupervised word segmentation

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Figure

Figure 1: A sample parse generated by the “func-tion word” Adaptor Grammar with rules (10–18)and (22–30)
Figure 2: Token and lexicon (i.e., type) f-score on the Bernstein-Ratner (1987) corpus as a function oftraining data size for the baseline model, the model where “function words” can appear on the left pe-riphery, a model where “function words” can appear
Figure 3: Bayes factor in favour of left-peripheral“function word” attachment as a function of thenumber of sentences in the training corpus, cal-culated using the Harmonic Mean estimator (seewarning in text).

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