Triple
T37356084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flavortown Market |
E927456
|
entity |
| Predicate | partOfShowFormat |
P195992
|
FINISHED |
| Object | shopping-based cooking challenges |
—
|
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: shopping-based cooking challenges | Statement: [Flavortown Market, partOfShowFormat, shopping-based cooking challenges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfShowFormat Context triple: [Flavortown Market, partOfShowFormat, shopping-based cooking challenges]
-
A.
associatedShowFormat
chosen
Indicates that one entity (such as a show or program) is linked to a particular format or type of presentation it follows.
-
B.
playedFormat
Indicates that an entity (such as a game, show, or media content) is or was presented, delivered, or experienced in a particular format (such as digital, physical, live, or specific media type).
-
C.
awardShowFormat
Indicates the specific structure or style in which an award show is organized and presented.
-
D.
portrayalFormat
Indicates the medium or format in which something is portrayed or represented (e.g., painting, sculpture, film, digital).
-
E.
presentedInFormat
Indicates that something is expressed, delivered, or made available using a particular format or representation.
- 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_69f76eb701788190b40824bc4594d985 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a016777257081908841c5522dfa76e6 |
completed | May 11, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_6a0164e49bec8190af3c8626be9677a9 |
completed | May 11, 2026, 5:11 a.m. |
Created at: May 3, 2026, 4:16 p.m.