Triple
T6358713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California's 12th congressional district |
E143055
|
entity |
| Predicate | CookPVI |
P70180
|
FINISHED |
| Object | D+20 or stronger in many cycles |
—
|
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: D+20 or stronger in many cycles | Statement: [California's 12th congressional district, CookPVI, D+20 or stronger in many cycles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CookPVI Context triple: [California's 12th congressional district, CookPVI, D+20 or stronger in many cycles]
-
A.
hasCookPVI
Indicates that an entity serves as the primary visual illustration (e.g., main image) associated with a cooking-related item, recipe, or process.
-
B.
isCookedBy
Indicates that something has been prepared or made ready for eating through cooking by a particular agent.
-
C.
chef
Indicates that one entity serves as the cook or culinary professional responsible for preparing food for another entity or context.
-
D.
isUsuallyCookedIn
Indicates that something is most commonly or typically prepared or cooked within a particular container, appliance, or environment.
-
E.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
- 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f72f8481908f9df0c0cdf22a52 |
completed | March 22, 2026, 10:06 p.m. |
| PD | Predicate disambiguation | batch_69c060ec091c8190912aac44e1b8b1c9 |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623bb29081908bfdfb84a07ece90 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:32 p.m.