Triple
T3204777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | If |
E67134
|
entity |
| Predicate | songwriter |
P1141
|
FINISHED |
| Object | Wayne Garfield |
E335204
|
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: Wayne Garfield | Statement: [If, songwriter, Wayne Garfield]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wayne Garfield Context triple: [If, songwriter, Wayne Garfield]
-
A.
Wayne Garfield
chosen
Wayne Garfield is a songwriter best known for his work on the Janet Jackson hit "All for You."
-
B.
Douglas Wick
Douglas Wick is an American film producer known for acclaimed movies such as "Gladiator," "Working Girl," and "Memoirs of a Geisha."
-
C.
Wylie Gelber
Wylie Gelber is an American musician best known as the bassist and a founding member of the indie rock band Dawes.
-
D.
Jeff Pidgeon
Jeff Pidgeon is an American animator, storyboard artist, and voice actor best known for his work at Pixar on films such as Monsters, Inc. and the Toy Story series.
-
E.
Fred Karger
Fred Karger was an American musician and vocal coach best known for his work at major Hollywood studios and his long, on-and-off marriage to actress Jane Wyman.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69adaa559848819082d1e61f586278dd |
completed | March 8, 2026, 4:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b27707577481909be867ffdb63d3b8 |
completed | March 12, 2026, 8:19 a.m. |
Created at: March 8, 2026, 3:07 p.m.