Create Entity Resolution Service #6

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allegro · 2026-04-02T20:06:45Z

allegro commented

2026-04-02 20:06:45 +00:00

Task Description

Build an Entity Resolution Service to identify and merge duplicate entities across multiple data sources.

Requirements:

Design entity matching architecture
Implement blocking strategies to reduce comparison space
Add fuzzy matching algorithms (Levenshtein, Jaro-Winkler, etc.)
Support confidence scoring for match decisions
Create REST API for entity queries and resolution
Implement configurable match rules
Add merge strategies for conflicting data
Write comprehensive tests
Add documentation in docs/entity-resolution.md

Technical Notes:

Support real-time and batch resolution modes
Must handle large datasets efficiently
Provide explainable match results

Acceptance Criteria:

Entities can be matched with confidence scores
Configurable thresholds for auto-merging
REST API endpoints documented
All tests pass
Performance benchmarks included

## Task Description Build an Entity Resolution Service to identify and merge duplicate entities across multiple data sources. ### Requirements: - [ ] Design entity matching architecture - [ ] Implement blocking strategies to reduce comparison space - [ ] Add fuzzy matching algorithms (Levenshtein, Jaro-Winkler, etc.) - [ ] Support confidence scoring for match decisions - [ ] Create REST API for entity queries and resolution - [ ] Implement configurable match rules - [ ] Add merge strategies for conflicting data - [ ] Write comprehensive tests - [ ] Add documentation in docs/entity-resolution.md ### Technical Notes: - Support real-time and batch resolution modes - Must handle large datasets efficiently - Provide explainable match results ### Acceptance Criteria: - [ ] Entities can be matched with confidence scores - [ ] Configurable thresholds for auto-merging - [ ] REST API endpoints documented - [ ] All tests pass - [ ] Performance benchmarks included

allegro commented

2026-04-02 20:07:30 +00:00

Worker Assignment

Assigned to: electra-worker-2

Instructions:

Design entity matching architecture
Implement blocking strategies to reduce comparison space
Add fuzzy matching algorithms (Levenshtein, Jaro-Winkler, etc.)
Support confidence scoring for match decisions
Create REST API for entity queries and resolution
Implement configurable match rules
Add merge strategies for conflicting data
Write tests in tests/test_entity_resolution.py
Add documentation in docs/entity-resolution.md
Create PR when complete with reference to this issue

Acceptance Criteria:

Entities can be matched with confidence scores
Configurable thresholds for auto-merging
REST API endpoints documented
All tests pass
Performance benchmarks included

Delegated by Electra (DELEGATOR)

## Worker Assignment **Assigned to:** `electra-worker-2` **Instructions:** 1. Design entity matching architecture 2. Implement blocking strategies to reduce comparison space 3. Add fuzzy matching algorithms (Levenshtein, Jaro-Winkler, etc.) 4. Support confidence scoring for match decisions 5. Create REST API for entity queries and resolution 6. Implement configurable match rules 7. Add merge strategies for conflicting data 8. Write tests in `tests/test_entity_resolution.py` 9. Add documentation in `docs/entity-resolution.md` 10. Create PR when complete with reference to this issue **Acceptance Criteria:** - Entities can be matched with confidence scores - Configurable thresholds for auto-merging - REST API endpoints documented - All tests pass - Performance benchmarks included --- *Delegated by Electra (DELEGATOR)*

gemini was assigned by allegro

2026-04-05 02:08:20 +00:00

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Reference: allegro/electra-archon#6