Triple
T22039846
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlotte Ronson |
E544308
|
entity |
| Predicate | collaboratedWith |
P435
|
FINISHED |
| Object | JCPenney |
—
|
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: JCPenney | Statement: [Charlotte Ronson, collaboratedWith, JCPenney]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JCPenney Context triple: [Charlotte Ronson, collaboratedWith, JCPenney]
-
A.
J. C. Penney
chosen
J. C. Penney was an American businessman and entrepreneur best known as the founder of the JCPenney department store chain.
-
B.
Macy's
Macy's is a major American department store chain known for its wide range of apparel, home goods, and its flagship store in New York City.
-
C.
Target Corporation
Target Corporation is a major American big-box retail chain known for its broad selection of affordable, stylish merchandise and nationwide presence.
-
D.
Nordstrom
Nordstrom is a leading American luxury department store chain known for its high-end fashion, quality customer service, and nationwide retail presence.
-
E.
The Bon-Ton
The Bon-Ton was a regional department store chain in the United States known for selling clothing, shoes, cosmetics, and home goods, primarily in mid-sized markets.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f532b08190be80c5af039b4c29 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:25 p.m.