Triple
T7834444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue City |
E181654
|
entity |
| Predicate | touristPerception |
P68309
|
FINISHED |
| Object | photogenic destination |
—
|
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: photogenic destination | Statement: [Blue City, touristPerception, photogenic destination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristPerception Context triple: [Blue City, touristPerception, photogenic destination]
-
A.
tourismAttitude
chosen
Indicates the stance, perception, or disposition that an entity holds toward tourism or tourist activities.
-
B.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
C.
touristAccess
Indicates that a place or resource is available for use or visitation by tourists.
-
D.
tourismImportance
Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
-
E.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
- 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb064b872081908e269f4fe1b85436 |
completed | March 30, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:45 p.m.