Triple
T27987095
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portraits of Kiki de Montparnasse |
E706771
|
entity |
| Predicate | hasSubjectRelationship |
P84787
|
FINISHED |
| Object | muse and lover |
—
|
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 and lover | Statement: [Portraits of Kiki de Montparnasse, hasSubjectRelationship, muse and lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectRelationship Context triple: [Portraits of Kiki de Montparnasse, hasSubjectRelationship, muse and lover]
-
A.
hasCreatorRelationshipToSubject
Indicates that an entity stands in a creator role with respect to the subject, meaning it is responsible for bringing the subject into existence or producing it.
-
B.
hasAuthorRelationshipToSubject
Indicates that an entity serves as the author or creator of the specified subject.
-
C.
hasHumanSubject
Indicates that an entity serves as the human participant or subject involved in an action, event, or relation.
-
D.
associatedWithSubject
Indicates a general relationship or connection between an entity and a subject, without specifying the exact nature of that association.
-
E.
subjectRelation
chosen
Indicates that one entity stands in a specified relational role or connection to another entity.
- 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_69ef96b8b8d88190bad5e4ae966bf14e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fcec5f8b448190b48330a19b462d24 |
completed | May 7, 2026, 7:47 p.m. |
| PD | Predicate disambiguation | batch_69fceaf1e23881908ca24160a638e329 |
completed | May 7, 2026, 7:41 p.m. |
Created at: April 27, 2026, 7:48 p.m.