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Recipes for automatic text summarization using Google BERT and Microsoft UniLM
- Der_Einzige 7y agoAs someone whose extremely interested in this domain. I am excited to see these models productized. Are the pretrained extractive models able to create extractive summaries at the word level? Or are they (like most other extractive models) only selecting and ranking sentences?
- sharatsc 7y agoIt is at the token level. The length of the results can be changed.
- sharatsc 7y agohttps://techcommunity.microsoft.com/t5/ai-customer-engineering-team/bootstrap-your-text-summarization-solution-with-the-latest/ba-p/1268809 https://techcommunity.microsoft.com/t5/ai-customer-engineeri...
- Der_Einzige 7y agoIt looks like according to the notebook recepies that it's actually working at the sentence level (despite your claim). The way you train these is to mark a sentence as "1" or "0" based on if it's selected. Oh well, the world waits longer for a word-level (willing to skip around in sentences) and grammatically correct extractive summarizer. You got my hopes up though. https://github.com/microsoft/nlp-recipes/blob/master/examples/text_summarization/extractive_summarization_cnndm_transformer.ipynb https://github.com/microsoft/nlp-recipes/blob/master/example... My (failed) attempt to build what I was actually looking for: https://github.com/Hellisotherpeople/CX_DB8 https://github.com/Hellisotherpeople/CX_DB8