Triple
T13414613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nanxi River |
E313177
|
entity |
| Predicate | touristRegionFor |
P3030
|
FINISHED |
| Object | domestic tourists in China |
—
|
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: domestic tourists in China | Statement: [Nanxi River, touristRegionFor, domestic tourists in China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristRegionFor Context triple: [Nanxi River, touristRegionFor, domestic tourists in China]
-
A.
tourismRegion
chosen
Indicates that a place or area is designated or recognized as a tourism region associated with another geographic or administrative entity.
-
B.
connectsToTouristRegion
Indicates that one entity has a direct linkage or association to a tourist region, such as through location, access, or service provision.
-
C.
typicalDestinationsRegion
Indicates that a region is a common or characteristic destination area associated with something (such as travelers, routes, or activities).
-
D.
alsoAttractsTouristsIn
Indicates that a place, in addition to another, draws or appeals to tourists within a specified location or context.
-
E.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaeb556948190af008c88e5bbf051 |
completed | April 12, 2026, 2:39 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:39 p.m.