Triple
T5145270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bugsy & Meyer’s Steakhouse |
E116054
|
entity |
| Predicate | ambiance |
P30942
|
FINISHED |
| Object | vintage |
—
|
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: vintage | Statement: [Bugsy & Meyer’s Steakhouse, ambiance, vintage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ambiance Context triple: [Bugsy & Meyer’s Steakhouse, ambiance, vintage]
-
A.
ambientSpace
Indicates the surrounding or containing space within which an object, structure, or geometric entity is situated or defined.
-
B.
hasAmbience
chosen
Indicates that one entity provides or is characterized by a particular atmosphere, mood, or environmental quality experienced in or around another entity.
-
C.
aspect
Indicates a specific temporal phase or manner in which an action, event, or state unfolds or is viewed (e.g., ongoing, completed, habitual).
-
D.
around
Indicates that one entity is located or moves on all or most sides of another entity, encircling or surrounding it spatially.
-
E.
typicalChamber
Indicates that something is a standard or characteristic chamber associated with a given context or entity.
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd78d7f4d081908d59adcd86f52f1d |
completed | March 20, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69bd77ae2f10819098bb8939106e1281 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:43 p.m.