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Are there any pretrained NLP models or even analytical techniques to classify or score sentences from election speech into "implemented" and "future promise" categories.

Essentially, we aim to distinguish between text that describes something that has already been implemented or achieved and text that describes something with potential or promise for the future.

e.g. For "implemented" category:

  • Since our regime from last 5 years, we have ensured your village has 24 x 7 electricity.

e.g. For "future promise" category:

  • If we get elected, we will bring 24 x 7 electricity in your region.
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You can consider supplementing your current analysis with tense calculations such as the nltk POS tagging with the VBC (conditional future) and VBF (future) tags. This SOF question Determining tense of a sentence Python seems to be similar and has answers that could be helpful.

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