Triple
T26718355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ban Koh Larn |
E673627
|
entity |
| Predicate | tourismDestinationFor |
P21947
|
FINISHED |
| Object | international tourists |
—
|
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: international tourists | Statement: [Ban Koh Larn, tourismDestinationFor, international tourists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismDestinationFor Context triple: [Ban Koh Larn, tourismDestinationFor, international tourists]
-
A.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
-
B.
tourismRegion
Indicates that a place or area is designated or recognized as a tourism region associated with another geographic or administrative entity.
-
C.
journeyDestination
chosen
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
D.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
E.
countryTourismCategory
Indicates the tourism classification or category assigned to a country based on its tourism characteristics or status.
- 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_69eecda481d08190aea69f2f7c745f56 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620debeb48190b7db395fb86cf8d9 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 3:39 a.m.