Triple
T14948783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utoro |
E372735
|
entity |
| Predicate | hasTouristFacilityType |
P55845
|
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: [Utoro, hasTouristFacilityType, hotels]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristFacilityType Context triple: [Utoro, hasTouristFacilityType, hotels]
-
A.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
B.
hasTourismResource
chosen
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
C.
hasAttractionType
Indicates that one entity is associated with a specific kind or category of attraction (e.g., tourist, cultural, natural).
-
D.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
-
E.
hasCulturalFacilityType
Indicates that an entity has or is associated with a specific type of cultural facility (such as a museum, theater, or gallery).
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68fae3c81909873b113bfcaca05 |
completed | April 15, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69de9a588c2c8190b1245a1c406f447c |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:39 a.m.