Triple
T9800819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Card |
E237830
|
entity |
| Predicate | creditBureau |
P30059
|
FINISHED |
| Object | Equifax |
E14065
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Equifax | Statement: [Apple Card, creditBureau, Equifax]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Equifax Context triple: [Apple Card, creditBureau, Equifax]
-
A.
Equifax
chosen
Equifax is one of the three major U.S. credit reporting agencies, providing consumer credit information and related financial services worldwide.
-
B.
Experian
Experian is a global consumer credit reporting agency that collects and analyzes financial data to provide credit scores and related services to individuals and businesses.
-
C.
TransUnion
TransUnion is one of the three major U.S. credit reporting agencies, providing consumer credit reports, risk scores, and related financial data services to lenders and businesses worldwide.
-
D.
Acxiom
Acxiom is a global data and marketing technology company known for providing consumer data, analytics, and audience targeting solutions to businesses.
-
E.
Alliance Data Systems
Alliance Data Systems is a U.S.-based provider of data-driven marketing, loyalty, and private-label credit card services for retailers and other consumer-facing businesses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca84dd4608819097ff4ed00feca280 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda62a11a88190880e0cce24923b14 |
completed | April 1, 2026, 11:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1d5abb26c81909d597b65f24f9bcf |
completed | April 5, 2026, 3:23 a.m. |
Created at: March 30, 2026, 8:29 p.m.