Triple
T32362393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymonda, Op. 57 |
E826898
|
entity |
| Predicate | principalFemaleRole |
P173057
|
FINISHED |
| Object | Raymonda |
—
|
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: Raymonda | Statement: [Raymonda, Op. 57, principalFemaleRole, Raymonda]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: principalFemaleRole Context triple: [Raymonda, Op. 57, principalFemaleRole, Raymonda]
-
A.
femaleRole
Indicates that the role, function, or position involved is associated with or designated as female.
-
B.
leadFemaleRoleType
chosen
Indicates that an entity holds or is associated with the primary female leading role type in a work or production.
-
C.
principalRoleIn
Indicates that an entity holds the primary or leading role in a particular context, activity, or relationship.
-
D.
primaryActor
Indicates that the referenced entity is the main participant or most central party responsible for the action or event in the relationship.
-
E.
femaleLeadCharacterStatus
Indicates the narrative or role status assigned to a female lead character within a story or production.
- 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_69f34915a2588190bb3178f5ec2f48f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c1bb5f248190834161b5a6ba1ece |
completed | May 3, 2026, 3:32 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:49 a.m.