Triple
T18316563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York City cuisine |
E438764
|
entity |
| Predicate | dietaryDiversity |
P34157
|
FINISHED |
| Object | offers kosher options |
—
|
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: offers kosher options | Statement: [New York City cuisine, dietaryDiversity, offers kosher options]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dietaryDiversity Context triple: [New York City cuisine, dietaryDiversity, offers kosher options]
-
A.
feedingHabitDiversity
Indicates the variety and range of different feeding habits or dietary strategies exhibited by an entity.
-
B.
animalDietProvided
Indicates that food appropriate to an animal’s dietary needs is supplied to it.
-
C.
dietaryOptions
chosen
Indicates the types of diets or food-related preferences, restrictions, or choices that are applicable to or offered for an entity.
-
D.
characterizesDietAs
Indicates that one entity describes, defines, or assigns the type or nature of another entity’s diet.
-
E.
includesSpeciesWithDiet
Indicates that a group, area, or collection contains at least one species characterized by a specified type of diet.
- 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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5021e61008190a300b6c51976a837 |
completed | April 19, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.