Triple
T37247316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Phyllis Diller Show |
E923892
|
entity |
| Predicate | leadCharacterIsWidowedMother |
P186690
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [The Phyllis Diller Show, leadCharacterIsWidowedMother, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadCharacterIsWidowedMother Context triple: [The Phyllis Diller Show, leadCharacterIsWidowedMother, true]
-
A.
isWidowedFatherOf
Indicates that a person is the father of another person and that his spouse has died, leaving him widowed.
-
B.
isMaternalFigureOf
Indicates a nurturing, protective, and guiding parental-like relationship that one individual has toward another, typically in a motherly role.
-
C.
hasWidowProtagonist
chosen
Indicates that the main character in the work is a widow.
-
D.
marriedToUntilDeathOfSpouse
Indicates a marital relationship that is intended to remain in effect until the death of one of the spouses.
-
E.
isMotherOf
Indicates that one entity is the female parent who has given birth to or legally/ socially parents the other entity.
- 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.