Triple
T72126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greek American |
E1443
|
entity |
| Predicate | associatedCuisine |
P1016
|
FINISHED |
| Object | gyros |
—
|
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: gyros | Statement: [Greek American, associatedCuisine, gyros]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedCuisine Context triple: [Greek American, associatedCuisine, gyros]
-
A.
traditionalCuisine
chosen
Indicates that an entity is associated with the customary or historically rooted style of cooking and food preparation characteristic of a particular culture, region, or community.
-
B.
widelyCultivatedIn
Indicates that something is grown extensively or on a large scale within a particular place or region.
-
C.
typicalFlavor
Indicates that something characteristically has or is associated with a particular flavor.
-
D.
notablyAssociatedWith
Indicates that one entity is prominently or distinctively connected with another in a way that is especially noteworthy or remarkable.
-
E.
relatedCountry
Indicates that there is a relevant or associated relationship between an entity and a specified country, without specifying the exact nature of that relationship.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24f6997c081908b202f937eb2b14f |
completed | Feb. 28, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69a24eab7f408190a8275cb82474f575 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.