Triple
T35746363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sadan Cave |
E1033192
|
entity |
| Predicate | tourismPopularity |
P20205
|
FINISHED |
| Object | well-known attraction in Kayin State |
—
|
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: well-known attraction in Kayin State | Statement: [Sadan Cave, tourismPopularity, well-known attraction in Kayin State]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismPopularity Context triple: [Sadan Cave, tourismPopularity, well-known attraction in Kayin State]
-
A.
hasTouristPopularity
chosen
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
-
B.
tourismTrend
Indicates how patterns or levels of tourism activity change over time or across locations.
-
C.
touristAttractionRanking
Indicates the relative position or level of appeal assigned to a tourist attraction compared to others, typically based on popularity, quality, or significance.
-
D.
shareTourismFlows
Indicates that two places are connected by or exchange significant tourism flows, such as visitors or tourist traffic, between them.
-
E.
tourismBoom
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
- 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_69f76e119d508190a3873cb302063832 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a193bec481909a83b202d36d5e3d |
completed | May 3, 2026, 7:27 p.m. |
| PD | Predicate disambiguation | batch_69f7a070e23881909a233370acb57384 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:06 p.m.