Triple
T44874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Restaurant School at Walnut Hill College |
E881
|
entity |
| Predicate | hasFacilityType |
P2836
|
FINISHED |
| Object | teaching kitchens |
—
|
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: teaching kitchens | Statement: [The Restaurant School at Walnut Hill College, hasFacilityType, teaching kitchens]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacilityType Context triple: [The Restaurant School at Walnut Hill College, hasFacilityType, teaching kitchens]
-
A.
hasNotableFacility
Indicates that an entity possesses or hosts a facility that is of particular significance, prominence, or interest.
-
B.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
C.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
D.
plannedFacility
Indicates that a facility is intended or scheduled to be built, established, or implemented in the future but does not yet exist or operate.
-
E.
hasStationBuilding
Indicates that a station is associated with or includes a station building as part of its facilities.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24ba7016481909d595402712db6e2 |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24abbd32c81908cec461d9097662e |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24ba5da048190a484963cb5a9bb2b |
completed | Feb. 28, 2026, 1:57 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.