Triple
T26409685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louisiana Voodoo |
E663923
|
entity |
| Predicate | hasTouristAspect |
P55845
|
FINISHED |
| Object | New Orleans Voodoo 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: New Orleans Voodoo tourism | Statement: [Louisiana Voodoo, hasTouristAspect, New Orleans Voodoo tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristAspect Context triple: [Louisiana Voodoo, hasTouristAspect, New Orleans Voodoo tourism]
-
A.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
B.
hasTourismStyle
Indicates the type or style of tourism associated with or characteristic of a particular entity.
-
C.
hasTourismResource
chosen
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
D.
hasTourismPotential
Indicates that a place or resource possesses qualities that make it attractive or suitable for tourism activities or development.
-
E.
hasGoalForTourists
Indicates that something is intended or designed to achieve a specific objective or benefit for tourists.
- 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_69ee883931888190901be96d75ee23cc |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 26, 2026, 11:37 p.m.