feat: add opt-in fallback for attribute-style hub-entity queries#21
Merged
LuyaoZhuang merged 1 commit intoDEEP-PolyU:mainfrom Mar 4, 2026
Merged
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Closes #19
Summary
This PR adds a small, opt-in retrieval fallback for attribute-style queries (e.g. where/when/born/located/founded) while keeping LinearRAG default behavior unchanged.
What changed
src/config.py:enable_hybrid_attribute_fallback(defaultFalse)attribute_keyword_boost(default0.25)attribute_query_keywords(lightweight keyword list)src/LinearRAG.py:questioncontext into graph retrieval scoringWhy
Issue #19 reports hub-entity attribute queries retrieving broad/high-centrality passages while missing relation-specific information. This PR adds a graceful, optional mitigation without changing the paper-faithful default pipeline.
Validation
python3 -m py_compile src/LinearRAG.py src/config.py src/ner.py src/utils.pyenable_hybrid_attribute_fallback=False.If maintainers prefer, I can follow up with a tiny synthetic regression harness in a separate PR to quantify ranking changes on attribute-style examples.