nlp-recipes

From https://news.ycombinator.com/item?id=34659668 : >> How do the responses compare to auto-summarization in terms of Big E notation and usefulness? > Automatic summarization: https://en.wikipedia.org/wiki/Automatic_summarization > "Automatic summarization" GH topic: https://github.com/topics/automatic-summarization Though now archived, > Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content NLP Tasks: Text Classification, Named Entity Recognition, Text Summarization, Entailment, Question Answering, Sentence Similarity, Embeddings, Sentiment Analysis, Model Explainability, and Auto-Annotatiom

> How do the responses compare to auto-summarization in terms of Big E notation and usefulness? Automatic summarization: https://en.wikipedia.org/wiki/Automatic_summarization "Automatic summarization" GH topic: https://github.com/topics/automatic-summarization Microsoft/nlp-recipes lists current NLP tasks that would be helpful for a docs bot: https://github.com/microsoft/nlp-recipes#content https://github.com/microsoft/nlp-recipes#content

It 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/example... My (failed) attempt to build what I was actually looking for: https://github.com/Hellisotherpeople/CX_DB8