Triple
T22563084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yongtai County |
E557867
|
entity |
| Predicate | hasTouristResource |
P55845
|
FINISHED |
| Object | natural hot springs |
—
|
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: natural hot springs | Statement: [Yongtai County, hasTouristResource, natural hot springs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristResource Context triple: [Yongtai County, hasTouristResource, natural hot springs]
-
A.
hasTourismResource
chosen
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
B.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
C.
hasTouristRoute
Indicates that a location or site is connected to or included in a designated tourist route or itinerary.
-
D.
hasTouristInfrastructure
Indicates that a place is equipped with facilities and services designed to support and accommodate tourists.
-
E.
containsTouristArea
Indicates that a place or region includes within its boundaries an area primarily designated or recognized for tourism activities.
- 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_69e11e5ae4ac8190b1f503457603d969 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15fa7a828819096804ac928e2aaf9 |
completed | April 29, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69ee626e6bb08190ada4dd8b48cc0c43 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:52 p.m.