Papers with part-of-speech annotations

1 papers
Categorial Grammar Induction with Stochastic Category Selection (2024.lrec-main)

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Challenge: categorial grammar inducers have been used to learn from raw data, but they use shortcuts to ensure branching behavior.
Approach: They propose a grammar inducer that learns from raw data and does not rely on bias terms . they show a recall-homogeneity of 0.48 on a corpus of English child-directed speech .
Outcome: The proposed model achieves a recall-homogeneity of 0.48 on a corpus of English child-directed speech .

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