Triple
T5142394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A24 |
E115987
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Daniel Katz |
E372221
|
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: Daniel Katz | Statement: [A24, foundedBy, Daniel Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Katz Context triple: [A24, foundedBy, Daniel Katz]
-
A.
Daniel Katz
chosen
Daniel Katz is an environmental activist and social entrepreneur best known for co-founding the Rainforest Alliance, a leading international conservation and sustainability organization.
-
B.
Don Katz
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
-
C.
Jason Katz
Jason Katz is an American screenwriter and story artist best known for his work on Pixar animated films.
-
D.
Daniel Goldberg
Daniel Goldberg is a Canadian film producer best known for his long-running collaboration with Ivan Reitman on comedies such as "Meatballs," "Stripes," and "Old School."
-
E.
Daniel Melnick
Daniel Melnick was an American film and television producer known for overseeing influential movies such as “Network,” “All That Jazz,” and “Altered States.”
- 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_69bd4446c0e08190a7c29dc74976bf03 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd787ff1c081909a6954aa76e12cbf |
completed | March 20, 2026, 4:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c059bd73e481909e23e1796262b8c4 |
completed | March 22, 2026, 9:06 p.m. |
Created at: March 20, 2026, 1:43 p.m.