Triple
T7419309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Da Real World |
E171203
|
entity |
| Predicate | performerGenderOfArtist |
P20803
|
FINISHED |
| Object | female |
—
|
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: female | Statement: [Da Real World, performerGenderOfArtist, female]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: performerGenderOfArtist Context triple: [Da Real World, performerGenderOfArtist, female]
-
A.
hasPerformerGender
chosen
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
B.
performerType
Indicates the role or category of performer responsible for carrying out an action or participating in an event.
-
C.
playsGender
Indicates that one entity performs or assumes a particular gender role or identity in a given context.
-
D.
featuredGender
Indicates that a particular gender is highlighted, emphasized, or given primary focus in a given context or presentation.
-
E.
hasGenderOfPerson
Indicates that a person is associated with a specific gender classification.
- 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_69c68a625d048190af70eb8b63bec5a0 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2e93ffc8190beb5a1d3eb6c5d23 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.