Triple
T22198845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juno (2007 film) |
E548619
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object | Mr. Mudd |
—
|
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: Mr. Mudd | Statement: [Juno (2007 film), productionCompany, Mr. Mudd]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Mudd Context triple: [Juno (2007 film), productionCompany, Mr. Mudd]
-
A.
Mr. Mudd
chosen
Mr. Mudd is a film and television production company known for producing acclaimed independent and character-driven projects.
-
B.
Mr. Franks
Mr. Franks is a music producer best known for his work with the hip-hop collective Legend.
-
C.
Mickey Goldmill
Mickey Goldmill is the gruff, old-school boxing trainer and mentor of Rocky Balboa in the "Rocky" film series.
-
D.
Mr. Jinks
Mr. Jinks is a Hanna-Barbera cartoon cat best known from "The Huckleberry Hound Show," where he comically schemes against the mischievous mice Pixie and Dixie.
-
E.
Alvin Marsh
Alvin Marsh is a character from Stephen King's novel "It," known as Beverly Marsh's abusive and controlling father.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12ae98808819081582a57bca6312b |
completed | April 28, 2026, 9:47 p.m. |
Created at: April 16, 2026, 8:36 p.m.