Triple
T29039928
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Betty Hutton Show |
E737966
|
entity |
| Predicate | leadActorOccupationInStory |
P110410
|
FINISHED |
| Object | former showgirl |
—
|
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: former showgirl | Statement: [The Betty Hutton Show, leadActorOccupationInStory, former showgirl]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorOccupationInStory Context triple: [The Betty Hutton Show, leadActorOccupationInStory, former showgirl]
-
A.
leadActorOccupation
chosen
Indicates that the occupation specified is the primary professional role of the lead actor in a given work or context.
-
B.
leadRoleActor
Indicates that an actor performs a leading or principal role in a work or production.
-
C.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
-
D.
originalLeadActorRole
Indicates the role originally played by a particular lead actor in a given production or work.
-
E.
otherProtagonistOccupation
Indicates that another main character in the narrative has a specific occupation or job role.
- 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_69f077efb3848190b41574e1670f6ae2 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f674e06c9481909ed0ea736408f0d7 |
completed | May 2, 2026, 10:04 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
Created at: April 28, 2026, 10:01 a.m.