Triple
T29801926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | After the Rain pas de deux |
E756728
|
entity |
| Predicate | originalFemaleLead |
P6108
|
FINISHED |
| Object | Wendy Whelan |
—
|
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: Wendy Whelan | Statement: [After the Rain pas de deux, originalFemaleLead, Wendy Whelan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalFemaleLead Context triple: [After the Rain pas de deux, originalFemaleLead, Wendy Whelan]
-
A.
leadFemaleRoleType
Indicates that an entity holds or is associated with the primary female leading role type in a work or production.
-
B.
originalMaleLeadRole
Indicates that an entity was the first male actor to play a particular leading role in a work or production.
-
C.
leadActress
chosen
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
D.
femaleLeadCharacterStatus
Indicates the narrative or role status assigned to a female lead character within a story or production.
-
E.
relationshipTypeWithFemaleLead
Indicates the type or nature of a relationship that an entity has with a female lead.
- 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_69f2245584848190ad4cab1f07752ccb |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69ffc89596d08190b97bd60b45c7f9c0 |
completed | May 9, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69ffc81ba5dc8190ae94d44e2284948f |
completed | May 9, 2026, 11:49 p.m. |
Created at: April 29, 2026, 5:18 p.m.