# Sentence coverage
**URL:** https://community.pinecone.io/t/sentence-coverage/211
**Category:** General
**Tags:** sentence-transformer
**Created:** [February 8, 2022, 8:53am UTC](https://community.pinecone.io/t/sentence-coverage/211 "2022-02-08T08:53:30Z")
**Posts on this page:** 2
**Page:** 1
### Author:  [@Laura](https://community.pinecone.io/u/Laura)
#### Post date: [February 8, 2022, 8:53am UTC](https://community.pinecone.io/t/sentence-coverage/211/1 "2022-02-08T08:53:30Z")
Is it possible to use SBERT models to understand the extent of coverage of a query sentence across the whole document? For example, if a query sentence consists of ‘X and Y’ and one sentence in the document refers to ‘X’ and a separate sentence somewhere else in the document refers to ‘Y’. Or is the best you can do is just return document sentence 1 and 2 as vaguely similar sentences?
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### Author:  [@jamesbriggs](https://community.pinecone.io/u/jamesbriggs)
#### Post date: [February 8, 2022, 2:29pm UTC](https://community.pinecone.io/t/sentence-coverage/211/2 "2022-02-08T14:29:47Z")
You can encode all of the sentences in the document using SBERT and then perform a similarity search with sentence X and return the most similar other sentences in the document, say the top 100 most similar, and set a similarity threshold where any sentences over the threshold you classify as relevant and anything below is discarded.