Triple
T16132755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JobServe Community Stadium |
E391440
|
entity |
| Predicate | hasFoodAndDrinkKiosks |
P70493
|
FINISHED |
| Object | yes |
—
|
LITERAL 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: yes | Statement: [JobServe Community Stadium, hasFoodAndDrinkKiosks, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFoodAndDrinkKiosks Context triple: [JobServe Community Stadium, hasFoodAndDrinkKiosks, yes]
-
A.
hasFoodVendors
Indicates that one entity provides or hosts food vendors that operate at or within another entity.
-
B.
offersFoodAndBeverage
chosen
Indicates that an entity provides both food and drink to another entity or for general consumption.
-
C.
hasFoodOption
Indicates that an entity offers, provides, or includes a particular type of food or dining option.
-
D.
hasFoodOrDrink
Indicates that an entity possesses, provides, or is associated with some type of food or drink.
-
E.
hasRestaurantsAndCafes
Indicates that the subject location contains or provides access to restaurants and cafés.
- F. None of above.
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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21a02e0048190b4e2c6ff434c2d7a |
completed | April 17, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69e182885bc08190822ae7e8a4b8ac1f |
completed | April 17, 2026, 12:44 a.m. |
Created at: April 10, 2026, 5:01 a.m.