Triple
T2007806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funny Face |
E43624
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Roger Edens |
E174656
|
NE FINISHED |
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: Roger Edens | Statement: [Funny Face, producer, Roger Edens]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roger Edens Context triple: [Funny Face, producer, Roger Edens]
-
A.
Roger Edens
chosen
Roger Edens was an American composer, arranger, and producer best known for his influential work on classic MGM musicals in Hollywood’s Golden Age.
-
B.
Frank Nighbor
Frank Nighbor was a pioneering early 20th-century Canadian ice hockey star renowned for his exceptional two-way play and sportsmanship in the National Hockey League.
-
C.
Ed Eagan
Ed Eagan is an American media executive best known for co-founding the sports television network ESPN.
-
D.
Gordon Howe
Gordon "Gordie" Howe was a legendary Canadian professional ice hockey player widely known as "Mr. Hockey" and regarded as one of the greatest players in the sport's history.
-
E.
Dan Dailey
Dan Dailey was an American actor and dancer best known for his roles in Hollywood musicals of the 1940s and 1950s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb89aca908190b8b659af65afdf6f |
completed | March 7, 2026, 5:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae1fe068ac8190b0999e4f881d134a |
completed | March 9, 2026, 1:18 a.m. |
Created at: March 4, 2026, 7:37 p.m.