Triple
T28127135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avengers Campus (Walt Disney Studios Park) |
E710957
|
entity |
| Predicate | hasFoodLocation |
P180417
|
FINISHED |
| Object | WEB Food Truck |
—
|
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: WEB Food Truck | Statement: [Avengers Campus (Walt Disney Studios Park), hasFoodLocation, WEB Food Truck]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFoodLocation Context triple: [Avengers Campus (Walt Disney Studios Park), hasFoodLocation, WEB Food Truck]
-
A.
eatenLocation
Indicates the place where an eating event occurs or where something is consumed.
-
B.
hasFoodOption
Indicates that an entity offers, provides, or includes a particular type of food or dining option.
-
C.
hasFoodOrDrink
Indicates that an entity possesses, provides, or is associated with some type of food or drink.
-
D.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
E.
hasStreetFood
Indicates that one entity offers, features, or is associated with street food in relation to another entity.
- F. None of above. chosen
Provenance (4 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_69ef9b73bd288190a21ae3d6aa14f386 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f74062b9388190b30546cf700a825c |
completed | May 3, 2026, 12:32 p.m. |
| PD | Predicate disambiguation | batch_69f73c802b848190b61a416b7488bd96 |
completed | May 3, 2026, 12:16 p.m. |
| PDg | Predicate description generation | batch_69f74061c440819080434155c2d60341 |
completed | May 3, 2026, 12:32 p.m. |
Created at: April 27, 2026, 9:20 p.m.