Triple
T15691455
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Self-Portrait with Harlequin |
E380339
|
entity |
| Predicate | reflectsInterestOfArtistIn |
P120299
|
FINISHED |
| Object | theatrical subjects |
—
|
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: theatrical subjects | Statement: [Self-Portrait with Harlequin, reflectsInterestOfArtistIn, theatrical subjects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reflectsInterestOfArtistIn Context triple: [Self-Portrait with Harlequin, reflectsInterestOfArtistIn, theatrical subjects]
-
A.
reflectsInterestOfAuthorIn
Indicates that something expresses or reveals the author’s interest in a particular subject, entity, or topic.
-
B.
subjectRelationToArtist
Indicates the nature of the relationship or connection that the subject has to the artist.
-
C.
representsArtist
Indicates that one entity serves as the artistic representative or agent for another artist entity.
-
D.
inspiredByArtist
Indicates that one entity’s work, style, or creation is influenced or motivated by the artistic output or persona of another artist.
-
E.
mentionsArtist
Indicates that one entity explicitly refers to or cites an artist in its content or context.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e0b4d6b5788190883746ee82c799f5 |
completed | April 16, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e0051d639481909a10614e8f83e659 |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e0b4d01c9c81909f6b611e8144c838 |
completed | April 16, 2026, 10:07 a.m. |
Created at: April 10, 2026, 4:44 a.m.