Triple
T10562496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libertà |
E249255
|
entity |
| Predicate | hasPerformerGenderMix |
P81870
|
FINISHED |
| Object | male-female duo |
—
|
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: male-female duo | Statement: [Libertà, hasPerformerGenderMix, male-female duo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerformerGenderMix Context triple: [Libertà, hasPerformerGenderMix, male-female duo]
-
A.
hasPerformerGenderComposition
chosen
Indicates the gender makeup of the group of performers involved in an event or performance.
-
B.
hasPerformerGender
Indicates that an action, event, or performance is associated with the gender of the performer who carries it out.
-
C.
hasNumberOfGenders
Indicates the relationship that specifies how many distinct genders are associated with or recognized for a given entity.
-
D.
hasHostGender
Indicates that an entity has or is associated with a specific gender of its host.
-
E.
hasNotablePerformerDuo
Indicates that the subject has a notable performing duo associated with it, such as a well-known pair of artists or entertainers who perform together.
- 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_69d381c8bd708190acf3d275c908251e |
completed | April 6, 2026, 9:50 a.m. |
| NER | Named-entity recognition | batch_69d527212dd081908629d91ce08f96a0 |
completed | April 7, 2026, 3:47 p.m. |
| PD | Predicate disambiguation | batch_69d51901ff6c819095e7b528170a69dc |
completed | April 7, 2026, 2:47 p.m. |
Created at: April 6, 2026, 12:36 p.m.