Triple
T1590144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Street Pavilion |
E34159
|
entity |
| Predicate | amenityType |
P5622
|
FINISHED |
| Object | hospitality services |
—
|
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: hospitality services | Statement: [State Street Pavilion, amenityType, hospitality services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amenityType Context triple: [State Street Pavilion, amenityType, hospitality services]
-
A.
amenity
chosen
Indicates that one entity provides a useful facility, service, or feature that enhances the convenience or comfort of another entity.
-
B.
amenityLevel
Indicates the degree or quality of facilities, services, or conveniences provided in relation to something.
-
C.
buildingType
Indicates the specific category or function that characterizes what kind of building something is.
-
D.
campusFacilityType
Indicates the specific kind of facility a campus location is classified as (e.g., library, laboratory, residence hall).
-
E.
placeType
Indicates the type or category of place associated with an entity (e.g., city, park, building).
- 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_69a885fceb2c8190b47e0f7c0aefbff0 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93aedd45c819085843ac843d640e8 |
completed | March 5, 2026, 8:12 a.m. |
| PD | Predicate disambiguation | batch_69a907bdc19081908c84c5c0aa09e282 |
completed | March 5, 2026, 4:34 a.m. |
Created at: March 4, 2026, 7:27 p.m.