Triple
T12049425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Katz |
E286875
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Don Katz |
E286875
|
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: Don Katz | Statement: [Don Katz, name, Don Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Katz Context triple: [Don Katz, name, Don Katz]
-
A.
Don Katz
chosen
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
-
B.
Charles Katz
Charles Katz was the defendant whose challenge to FBI wiretapping led to the landmark U.S. Supreme Court decision in Katz v. United States, which redefined Fourth Amendment protections for privacy.
-
C.
Daniel Katz
Daniel Katz is an environmental activist and social entrepreneur best known for co-founding the Rainforest Alliance, a leading international conservation and sustainability organization.
-
D.
Daniel Katz
Daniel Katz is a cinematographer known for his work on the darkly comedic horror film "Come to Daddy."
-
E.
Lewis Katz
Lewis Katz was an American businessman, philanthropist, and co-owner of the Philadelphia Inquirer known for his major charitable contributions to education and medicine.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d904227958819084dbd5eb2566c735 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716afa8008190b4c518dd6004d87a |
completed | May 3, 2026, 9:34 a.m. |
Created at: April 8, 2026, 9:47 p.m.