Triple
T36793410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pete Miller |
E909114
|
entity |
| Predicate | hasOnScreenInterviewStyle |
P105209
|
FINISHED |
| Object | mockumentary talking-head interviews |
—
|
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: mockumentary talking-head interviews | Statement: [Pete Miller, hasOnScreenInterviewStyle, mockumentary talking-head interviews]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOnScreenInterviewStyle Context triple: [Pete Miller, hasOnScreenInterviewStyle, mockumentary talking-head interviews]
-
A.
hasInterviews
Indicates that one entity conducts, contains, or is associated with interviews involving another entity.
-
B.
notableInterviewStyle
chosen
Indicates that one entity is particularly recognized for a distinctive or characteristic way of conducting interviews with others.
-
C.
usesInterviews
Indicates that one entity employs interviews as a method or tool in relation to another entity or process.
-
D.
hasScreenplayStyle
Indicates that an entity is associated with or characterized by a particular style or manner of screenplay writing.
-
E.
hasAuthorInterviewRole
Indicates that an entity participates in an interview in the role of an author.
- 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_69f76e7a937c81909ed7359641e670f6 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcf825ca7081909d06b0df33eb33f9 |
completed | May 7, 2026, 8:37 p.m. |
| PD | Predicate disambiguation | batch_69fcf42160f0819096812a8bf590875e |
completed | May 7, 2026, 8:20 p.m. |
Created at: May 3, 2026, 4:12 p.m.