Triple
T18056328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Nice |
E432047
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Don Murphy |
—
|
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: Don Murphy | Statement: [Mr. Nice, producer, Don Murphy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Murphy Context triple: [Mr. Nice, producer, Don Murphy]
-
A.
Don Murphy
chosen
Don Murphy is an American film producer best known for helping launch and produce the live-action Transformers film franchise.
-
B.
Dennis Murphy
Dennis Murphy was a screenwriter known for his work on the film "The Sergeant."
-
C.
Dennis Murphy
Dennis Murphy was an American sports entrepreneur best known for co-founding several upstart professional leagues, including the American Basketball Association.
-
D.
Dennis Murphy
Dennis Murphy is an American television journalist best known as a longtime correspondent and host for NBC's newsmagazine program Dateline NBC.
-
E.
Phil Burke
Phil Burke is a Canadian actor best known for his role as Mickey McGinnes on the television drama series "Hell on Wheels."
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4c102d08081908d2419c898213400 |
completed | April 19, 2026, 11:48 a.m. |
Created at: April 10, 2026, 10:26 a.m.