Triple
T32081180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Imperia statue |
E819300
|
entity |
| Predicate | hasArtistResidence |
P128906
|
FINISHED |
| Object | Peter Lenk from Bodensee region |
—
|
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: Peter Lenk from Bodensee region | Statement: [Imperia statue, hasArtistResidence, Peter Lenk from Bodensee region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasArtistResidence Context triple: [Imperia statue, hasArtistResidence, Peter Lenk from Bodensee region]
-
A.
artistResidence
chosen
Indicates that a given location is the place where an artist lives or is based.
-
B.
hasResidentArtist
Indicates that one entity serves as the resident artist associated with or based at another entity.
-
C.
hasComposerResidence
Indicates that a composer has a particular place as their residence or primary dwelling.
-
D.
artistResidenceAtTimeOfWork
Indicates the place where an artist was living at the time a particular work was created.
-
E.
hasPerformerResidence
Indicates that a performer is associated with a particular place as their residence.
- 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_69f348ff8ef88190931c08ba530a36bc |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd49f6dbac81909744373a357b7982 |
completed | May 8, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69fd48ed68f481908374183c66a6b055 |
completed | May 8, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:24 a.m.