Triple
T1400330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 360 Restaurant |
E30764
|
entity |
| Predicate | hasDiningExperience |
P5308
|
FINISHED |
| Object | fine dining |
—
|
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: fine dining | Statement: [360 Restaurant, hasDiningExperience, fine dining]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningExperience Context triple: [360 Restaurant, hasDiningExperience, fine dining]
-
A.
hasMealType
Indicates that an entity is associated with a specific category or type of meal (such as breakfast, lunch, or dinner).
-
B.
diningStyle
Indicates the manner or format in which dining is conducted, such as casual, formal, buffet, or family-style.
-
C.
hasStapleFood
Indicates that an entity’s primary or regularly consumed basic food item is another specified entity.
-
D.
hasTypeOfVisitorExperience
chosen
Indicates that an entity is associated with a particular category or kind of visitor experience it provides or involves.
-
E.
eatenOnOccasion
Indicates that one entity is consumed or eaten by another only at certain times or under specific circumstances, rather than regularly or habitually.
- 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_69a498fd4e408190bd73eca30ea9754c |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c39c4c148190997150996ca26a99 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf017f8081908572121560ec621f |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.