Triple
T23482061
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Hubley |
E570430
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | John Hubley |
—
|
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: John Hubley | Statement: [John Hubley, name, John Hubley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Hubley Context triple: [John Hubley, name, John Hubley]
-
A.
John Hubley
chosen
John Hubley was an influential American animator and director known for his innovative work at UPA and for co-creating distinctive, modernist animated films and characters.
-
B.
Charles Gillibert
Charles Gillibert is a French film producer known for backing acclaimed auteur-driven films such as "Clouds of Sils Maria," "Personal Shopper," and "Mustang."
-
C.
Paul Lovett
Paul Lovett is a film screenwriter best known for co-writing the action drama movie "Four Brothers."
-
D.
Frank Parkinson
Frank Parkinson was a prominent British industrialist and philanthropist whose contributions to education led to major university buildings being named in his honor.
-
E.
Charles Aidman
Charles Aidman was an American character actor and voice artist best known for his extensive work in film and television from the 1950s through the 1980s.
- 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_69e245b0b01481908f636939bedd804c |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a75118048190b4af687906c4e747 |
completed | April 29, 2026, 6:38 a.m. |
Created at: April 17, 2026, 6:03 p.m.