Triple
T16486352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tusayan, Arizona |
E400450
|
entity |
| Predicate | hasLodgingType |
P112278
|
FINISHED |
| Object | hotels |
—
|
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: hotels | Statement: [Tusayan, Arizona, hasLodgingType, hotels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLodgingType Context triple: [Tusayan, Arizona, hasLodgingType, hotels]
-
A.
hasLodgeType
chosen
Indicates that an entity is associated with or classified by a particular type or category of lodge.
-
B.
hasHotelType
Indicates that a hotel is classified as belonging to a specific type or category (e.g., resort, boutique, hostel).
-
C.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
D.
hasResortType
Indicates that an entity (such as a resort or accommodation) is associated with a specific category or type of resort (e.g., beach resort, ski resort, spa resort).
-
E.
accommodationStyle
Indicates the manner or type of lodging or housing arrangement provided or used in a given context.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e068fac8190a0971f548848fcfe |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:13 a.m.