Triple
T18722716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leigh Bowery (Seated) |
E457816
|
entity |
| Predicate | subjectRoleForArtist |
P33013
|
FINISHED |
| Object | muse |
—
|
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: muse | Statement: [Leigh Bowery (Seated), subjectRoleForArtist, muse]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectRoleForArtist Context triple: [Leigh Bowery (Seated), subjectRoleForArtist, muse]
-
A.
subjectRelationToArtist
chosen
Indicates the nature of the relationship or connection that the subject has to the artist.
-
B.
hasArtistRole
Indicates that an entity serves in the capacity or role of an artist in relation to another entity or context.
-
C.
artistOccupation
Indicates the professional role or job that an artist holds or performs.
-
D.
featuresArtistAs
Indicates that one entity includes or presents another entity in the role of an artist (e.g., a work, event, or product featuring a specific artist).
-
E.
subjectLocationRelationToArtist
Indicates the spatial or locational relationship between a subject and an artist (e.g., where the subject is positioned relative to the artist).
- 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56abc1c708190917f6bfea0548c42 |
completed | April 19, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69e48d03766c8190a43f7681842f4f8d |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:50 a.m.