Triple
T20037661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everett Greenbaum |
E497318
|
entity |
| Predicate | wroteForSeries |
P36923
|
FINISHED |
| Object | Mister Peepers |
—
|
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: Mister Peepers | Statement: [Everett Greenbaum, wroteForSeries, Mister Peepers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mister Peepers Context triple: [Everett Greenbaum, wroteForSeries, Mister Peepers]
-
A.
Mr. Peepers
chosen
Mr. Peepers is a hyperactive, feral man-child character portrayed by Chris Kattan in sketches on Saturday Night Live.
-
B.
Peepers
Peepers is a character from the animated web series "Another Period," known for his role as the Bellacourt family's long-suffering butler.
-
C.
Mr. Pest
Mr. Pest is the bumbling, troublemaking character portrayed by Charlie Chaplin in the 1915 silent comedy film "A Night in the Show."
-
D.
Mr. Snoops
Mr. Snoops is a bumbling, cowardly henchman and treasure hunter who serves as one of the primary antagonists in Disney’s animated film "The Rescuers."
-
E.
The Mister
The Mister is a contemporary romance novel by E. L. James, known for its Cinderella-style love story and for being her follow-up to the Fifty Shades series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da627278c88190babe4297a9df1236 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e662e935ac8190900cdb4f0cfde505 |
completed | April 20, 2026, 5:31 p.m. |
Created at: April 11, 2026, 3:36 p.m.