Triple
T8822245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Vernon Marketplace |
E209932
|
entity |
| Predicate | cuisineDiversity |
P57962
|
FINISHED |
| Object | diverse |
—
|
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: diverse | Statement: [Mount Vernon Marketplace, cuisineDiversity, diverse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cuisineDiversity Context triple: [Mount Vernon Marketplace, cuisineDiversity, diverse]
-
A.
haveDistinctCulinaryTraditions
chosen
Indicates that the related entities possess different and distinguishable culinary practices, cuisines, or food-related customs from one another.
-
B.
cuisine
Indicates the type or style of food traditionally associated with or served by an entity (such as a restaurant or region).
-
C.
cuisineInfluence
Indicates that one cuisine has had a notable impact on the development, style, or characteristics of another cuisine.
-
D.
regionOfCulinaryImportance
Indicates that a location is recognized for its significant culinary relevance, such as notable food traditions, specialties, or gastronomic culture.
-
E.
cuisineType
Indicates the type or style of food associated with an entity, such as a restaurant or dish.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc602ed87c8190ab772e5cbb2da68d |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:46 p.m.