Triple
T20412695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joker Marchant Stadium |
E500627
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object | Publix |
—
|
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: Publix | Statement: [Joker Marchant Stadium, sponsor, Publix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Publix Context triple: [Joker Marchant Stadium, sponsor, Publix]
-
A.
Publix
chosen
Publix is a major employee-owned American supermarket chain based in the Southeastern United States.
-
B.
Winn-Dixie
Winn-Dixie is the friendly stray dog who becomes the beloved companion and catalyst for change in Kate DiCamillo’s children’s novel "Because of Winn-Dixie."
-
C.
Meijer
Meijer is a Dutch-origin surname borne by numerous individuals, including notable figures in business, politics, and the arts.
-
D.
Kroger
Kroger is one of the largest supermarket and retail grocery chains in the United States, operating thousands of stores under various banners nationwide.
-
E.
Harris Teeter
Harris Teeter is a regional American supermarket chain known for its grocery stores primarily located in the Southeastern and Mid-Atlantic United States.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a417f208190be9bc11650ee0a87 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:30 a.m.