Triple
T36915986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japan–United Kingdom relations |
E913045
|
entity |
| Predicate | tourismFlow |
P56675
|
FINISHED |
| Object | Japanese visitors to the United Kingdom |
—
|
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: Japanese visitors to the United Kingdom | Statement: [Japan–United Kingdom relations, tourismFlow, Japanese visitors to the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismFlow Context triple: [Japan–United Kingdom relations, tourismFlow, Japanese visitors to the United Kingdom]
-
A.
shareTourismFlows
chosen
Indicates that two places are connected by or exchange significant tourism flows, such as visitors or tourist traffic, between them.
-
B.
touristTraffic
Indicates the level, flow, or intensity of tourists visiting or moving through a particular place or area.
-
C.
tourismTrend
Indicates how patterns or levels of tourism activity change over time or across locations.
-
D.
touristArrivalsShareInTerritory
Indicates the proportion of total tourist arrivals that occur within a specific territory relative to a larger reference area or total.
-
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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb55ad44bc8190a802bdaab36adc94 |
completed | May 6, 2026, 2:52 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.