Triple
T22592024
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Affirm Holdings, Inc. |
E564973
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Jeff Kaditz |
—
|
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: Jeff Kaditz | Statement: [Affirm Holdings, Inc., foundedBy, Jeff Kaditz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Kaditz Context triple: [Affirm Holdings, Inc., foundedBy, Jeff Kaditz]
-
A.
Jeff Kaditz
chosen
Jeff Kaditz is an American entrepreneur and technologist best known as the co-founder and former CTO of the financial technology company Affirm.
-
B.
Michael Karpf
Michael Karpf is a British physician and academic leader best known for his roles in hospital administration and medical education.
-
C.
John Kamps
John Kamps is an American screenwriter best known for co-writing the family science fiction film "Zathura: A Space Adventure."
-
D.
Ken Lauber
Ken Lauber is an American composer and musician known for his film and television scores, blending elements of jazz, classical, and popular music.
-
E.
John Daheim
John Daheim was an American character actor who appeared in numerous film and television productions during the mid-20th century.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f16162c2cc8190a506776ac52356d7 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 2:49 p.m.