Triple
T18635979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny Pritzker |
E455547
|
entity |
| Predicate | boardMemberOf |
P10
|
FINISHED |
| Object | TransUnion |
—
|
NE NERFINISHED |
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: TransUnion | Statement: [Penny Pritzker, boardMemberOf, TransUnion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TransUnion Context triple: [Penny Pritzker, boardMemberOf, TransUnion]
-
A.
TransUnion
chosen
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.
-
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.
Equifax
Equifax is one of the three major U.S. credit reporting agencies, providing consumer credit information and related financial services worldwide.
-
D.
Credit Karma
Credit Karma is a personal finance company best known for offering free credit scores, credit monitoring, and tailored financial product recommendations to consumers.
-
E.
Acxiom
Acxiom is a global data and marketing technology company known for providing consumer data, analytics, and audience targeting solutions to businesses.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38cc7948190a55ea64e5638994e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e54fc90b508190849cecb462b52b62 |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 10, 2026, 11:46 a.m.