Triple
T31295727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Black Hat |
E798066
|
entity |
| Predicate | associatedWithArtistGender |
P207400
|
FINISHED |
| Object | woman artist |
—
|
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: woman artist | Statement: [The Black Hat, associatedWithArtistGender, woman artist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithArtistGender Context triple: [The Black Hat, associatedWithArtistGender, woman artist]
-
A.
associatedWithArtistType
Indicates that an entity has a connection or linkage to a particular category or type of artist.
-
B.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
C.
musicalArtistAssociated
Indicates a relationship where one musical artist is professionally connected or affiliated with another, such as through collaboration, membership, or frequent association.
-
D.
originalPerformerGender
Indicates the gender of the person who first performed or originated the work, role, or piece.
-
E.
associatedWithArtistGroup
Indicates that an entity has a relationship or connection with a particular artist group or collective.
- 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_69f224dfde288190af313f3c221c857e |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e5174c8190a0bdde7e381b7624 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 9:14 p.m.