Triple
T31650668
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little America Hotels |
E807721
|
entity |
| Predicate | hasHotelProperty |
P17960
|
FINISHED |
| Object | Little America Hotel Salt Lake City |
—
|
NE NERFINISHED |
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: Little America Hotel Salt Lake City | Statement: [Little America Hotels, hasHotelProperty, Little America Hotel Salt Lake City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotelProperty Context triple: [Little America Hotels, hasHotelProperty, Little America Hotel Salt Lake City]
-
A.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
B.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
C.
hasHospitalityComponent
Indicates that something includes, involves, or is associated with a hospitality-related element, service, or function.
-
D.
hasVenueProperty
Indicates that a venue possesses or is characterized by a specific property or attribute.
-
E.
hasAccommodation
chosen
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
- 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_69f348daf95c81908b4c985b7ddcd0b3 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fd09840ea88190a2e6d7e577ade717 |
completed | May 7, 2026, 9:52 p.m. |
| PD | Predicate disambiguation | batch_69fd064c49988190afadddbd04d7cb94 |
completed | May 7, 2026, 9:38 p.m. |
Created at: April 30, 2026, 10:53 p.m.