Triple
T24341259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Église Saint-Jean-Baptiste de Venoix |
E613516
|
entity |
| Predicate | hasFunctionalUse |
P144769
|
FINISHED |
| Object | place of worship |
—
|
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: place of worship | Statement: [Église Saint-Jean-Baptiste de Venoix, hasFunctionalUse, place of worship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFunctionalUse Context triple: [Église Saint-Jean-Baptiste de Venoix, hasFunctionalUse, place of worship]
-
A.
hasCommercialFunction
Indicates that an entity serves a commercial role or purpose, such as engaging in trade, sales, or other profit-oriented activities.
-
B.
hasPrimaryFunction
Indicates that one entity serves as the main or principal function or role of another entity.
-
C.
usesFunction
Indicates that one entity employs, invokes, or relies on a particular function to perform an operation or achieve a result.
-
D.
hasFacilityFunction
chosen
Indicates that a facility performs, supports, or is designated for a particular function or operational role.
-
E.
hasFictionalFunction
Indicates that an entity serves a role, purpose, or function within a fictional context or narrative.
- 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_69e2d7dcc5a08190b53691130d56cbc4 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2932511908190993ed984fdc4c739 |
completed | April 29, 2026, 11:24 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:57 a.m.