Triple
T27596094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | C.C. Babcock |
E699900
|
entity |
| Predicate | hasRunningGagWith |
P58285
|
FINISHED |
| Object | Niles the butler |
—
|
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: Niles the butler | Statement: [C.C. Babcock, hasRunningGagWith, Niles the butler]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRunningGagWith Context triple: [C.C. Babcock, hasRunningGagWith, Niles the butler]
-
A.
hasRecurringGag
Indicates that a particular joke, situation, or comedic element repeatedly appears in relation to an entity (such as a character, series, or work).
-
B.
notableGag
Indicates that something features a particularly memorable or significant joke, comedic moment, or running gag.
-
C.
featuresRunningGag
chosen
Indicates that the subject includes or makes use of a recurring joke or humorous motif.
-
D.
hasEvaluationGag
Indicates that an entity is subject to a restriction or prohibition on disclosing or sharing evaluations, assessments, or reviews related to it.
-
E.
reasonForRunningGag
Indicates the underlying cause or explanation for why a particular running gag recurs.
- 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_69ef6a4d71f081909a1235763206b691 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 27, 2026, 2:06 p.m.