How can NLTK be used to extract collocations for text generation purposes

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Can you tell me how NLTK can be used to extract collocations for text generation purposes? Use python code if possible.
Dec 16, 2024 in Generative AI by Ashutosh
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1 answer to this question.

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To extract collocations for text generation purposes using NLTK, you can use the BigramCollocationFinder and BigramAssocMeasures to identify frequent word pairs (collocations) from a corpus. Here is the code reference which you can refer to:

In the above code, we are using the following:

  • BigramCollocationFinder: Find pairs of words (bigrams) in the text.
  • BigramAssocMeasures.pmi: Measures the strength of the association between two words using Pointwise Mutual Information (PMI).
  • Text Generation: These collocations can be used to generate more natural text, as they represent common word pairs in the corpus.
The output of the above code would be:
Hence, this code extracts the most frequent and statistically significant bigram collocations from the Reuters corpus, which can be used in text generation models to produce more natural-sounding sentences.
answered Dec 16, 2024 by sania hoor

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