Triple
T17838024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commissary Lane |
E445443
|
entity |
| Predicate | hasDiningFocus |
P129370
|
FINISHED |
| Object | American cuisine |
—
|
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: American cuisine | Statement: [Commissary Lane, hasDiningFocus, American cuisine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDiningFocus Context triple: [Commissary Lane, hasDiningFocus, American cuisine]
-
A.
hasDiningFeature
Indicates that something possesses a specific characteristic, amenity, or attribute related to dining.
-
B.
hasDiningOptionType
Indicates that an entity offers or is associated with a specific type or category of dining option (e.g., dine-in, takeout, delivery).
-
C.
hasCharacterDining
Indicates that an entity offers or includes dining experiences where guests can eat while interacting with costumed characters.
-
D.
hasDiningPolicy
Indicates that an entity enforces or follows a specific set of rules or guidelines related to dining or meal-related activities.
-
E.
isDiningDestination
Indicates that a place serves as a destination where people go specifically to eat meals or dine.
- 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_69d8b9f1a6d881909f024bc603111cdb |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48d29830c81909fa3ef5a352921b8 |
completed | April 19, 2026, 8:07 a.m. |
| PD | Predicate disambiguation | batch_69e3d8e266888190ae976b4b7d5b886f |
completed | April 18, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69e3f022ec448190a9bf191be1c5f570 |
completed | April 18, 2026, 8:57 p.m. |
Created at: April 10, 2026, 10:16 a.m.