Triple
T29839485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Spectre de la rose |
E757745
|
entity |
| Predicate | originalFemaleLeadDancer |
P201239
|
FINISHED |
| Object | Tamara Karsavina |
—
|
NE NERFINISHED |
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: Tamara Karsavina | Statement: [Le Spectre de la rose, originalFemaleLeadDancer, Tamara Karsavina]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalFemaleLeadDancer Context triple: [Le Spectre de la rose, originalFemaleLeadDancer, Tamara Karsavina]
-
A.
originalMaleLeadDancer
Indicates that the subject is the first or primary male lead dancer originally associated with the referenced performance or production.
-
B.
leadActress
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
C.
originalQueenDancer
Indicates that an entity was an original member of the group of dancers performing with the musical act or production named "Queen."
-
D.
leadFemaleRoleType
Indicates that an entity holds or is associated with the primary female leading role type in a work or production.
-
E.
femaleLeadCharacterStatus
Indicates the narrative or role status assigned to a female lead character within a story or production.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69ffe01c9d3c819084c256bb3c81c0dc |
completed | May 10, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69ffdfcc78b08190aa4493f13d62a531 |
completed | May 10, 2026, 1:30 a.m. |
| PDg | Predicate description generation | batch_69ffe01be6e88190ac0742a5f74e769e |
completed | May 10, 2026, 1:32 a.m. |
Created at: April 29, 2026, 5:38 p.m.