Triple
T8773664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | God's Own Country |
E208523
|
entity |
| Predicate | tourismSegment |
P1769
|
FINISHED |
| Object | leisure tourism |
—
|
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: leisure tourism | Statement: [God's Own Country, tourismSegment, leisure tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismSegment Context triple: [God's Own Country, tourismSegment, leisure tourism]
-
A.
tourismType
chosen
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
B.
tourismMarket
Indicates a relationship where a location, service, or product functions as a destination or offering within the travel and tourism economy, attracting and serving tourists as a market segment.
-
C.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
D.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
E.
seasonalTourism
Indicates that tourism activity in a place varies significantly by season, with distinct peak and off-peak periods.
- 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2ef3288190988bd69e8a02e741 |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:41 p.m.