Triple
T37247315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Phyllis Diller Show |
E923892
|
entity |
| Predicate | starIsComedian |
P185309
|
FINISHED |
| Object | Phyllis Diller |
—
|
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: Phyllis Diller | Statement: [The Phyllis Diller Show, starIsComedian, Phyllis Diller]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: starIsComedian Context triple: [The Phyllis Diller Show, starIsComedian, Phyllis Diller]
-
A.
starsComedianKnownFor
Indicates that a work features a comedian who is particularly recognized or famous for that role or performance.
-
B.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
C.
hasLeadComedian
chosen
Indicates that one entity serves as the primary or main comedian associated with another entity, such as a show, event, or performance.
-
D.
starredActorWith
Indicates that one entity participated as an actor in a production together with another specified actor.
-
E.
comedian
Indicates that the subject performs comedy or is recognized for engaging in comedic entertainment.
- 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_69f76eaabb4c819093b751b139dad551 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb4134225081909fd60703b8cae397 |
completed | May 6, 2026, 1:25 p.m. |
| PD | Predicate disambiguation | batch_69fb35bf767081908de8345358ca7f44 |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:15 p.m.