Triple
T20919811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buzen |
E515174
|
entity |
| Predicate | tourismFeatures |
P33214
|
FINISHED |
| Object | coastal scenery |
—
|
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: coastal scenery | Statement: [Buzen, tourismFeatures, coastal scenery]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismFeatures Context triple: [Buzen, tourismFeatures, coastal scenery]
-
A.
tourismFeature
chosen
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
B.
tourismCharacteristic
Indicates that something has a specific feature, quality, or attribute relevant to tourism, such as what makes a place, service, or activity notable or suitable for tourists.
-
C.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
D.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
E.
tourismDraw
Indicates that one entity attracts tourists or visitor interest to another entity or 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_69e0b4f9d5ec8190bb2bd27350ed341c |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6ec677338819081410cbaa2846260 |
completed | April 21, 2026, 3:17 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:48 p.m.