Triple
T22185321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renoir family graves |
E548279
|
entity |
| Predicate | tourismMotivation |
P146749
|
FINISHED |
| Object | interest in Pierre-Auguste Renoir |
—
|
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: interest in Pierre-Auguste Renoir | Statement: [Renoir family graves, tourismMotivation, interest in Pierre-Auguste Renoir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismMotivation Context triple: [Renoir family graves, tourismMotivation, interest in Pierre-Auguste Renoir]
-
A.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
B.
tourismAttitude
Indicates the stance, perception, or disposition that an entity holds toward tourism or tourist activities.
-
C.
tourismTrend
Indicates how patterns or levels of tourism activity change over time or across locations.
-
D.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
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. chosen
Provenance (4 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aa823888190829368de6db4aa91 |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
| PDg | Predicate description generation | batch_69e7222e74248190a2d3671049f117f2 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:35 p.m.