Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Query biased document summary in PyTerrier #205

Closed
adambaker opened this issue Jul 7, 2021 · 3 comments
Closed

Query biased document summary in PyTerrier #205

adambaker opened this issue Jul 7, 2021 · 3 comments
Labels
enhancement New feature or request
Milestone

Comments

@adambaker
Copy link

I'm trying to extract text snippets for a search results page. I've found the documentation page for running terrier in a JSP, which describes some configuration for snippet extraction.

I'm still not sure how to use this in pyterrier. It seems like BatchRetrieve's properties or control parameters might be necessary to pass the required configuration, but then it's not clear to me how to get the query biased summary from the result set. Is there a way to do this with PyTerrier?

Thanks!

@adambaker adambaker added the enhancement New feature or request label Jul 7, 2021
@cmacdonald
Copy link
Contributor

cmacdonald commented Jul 21, 2021

Hi adam,

The query-biased summariser in Terrier is NOT that great. What about just breaking the text of the retrieved documents into sentences, and passing them through another text scoring ranking pipeline?

Craig

@cmacdonald
Copy link
Contributor

Adam, there is an draft PR for PyTerrier query biased summarisation at #223. We're not planning to merge for this week's PyT release, but it might be of interest.

@cmacdonald cmacdonald added this to the 0.8 milestone Jan 11, 2022
@cmacdonald
Copy link
Contributor

The corresponding PR has been merged - documentation at https://pyterrier.readthedocs.io/en/latest/text.html#query-biased-summarisation-snippets.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants