Triple
T12893393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Highest Duty |
E308426
|
entity |
| Predicate | author |
P4
|
FINISHED |
| Object | Jeffrey Zaslow |
E322942
|
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: Jeffrey Zaslow | Statement: [Highest Duty, author, Jeffrey Zaslow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeffrey Zaslow Context triple: [Highest Duty, author, Jeffrey Zaslow]
-
A.
Jeffrey Zaslow
chosen
Jeffrey Zaslow was an American author and journalist best known for co-authoring inspirational bestsellers such as "The Last Lecture" and other notable nonfiction works.
-
B.
Michael Zaslow
Michael Zaslow was an American actor best known for his long-running roles on daytime soap operas, particularly as complex, often villainous characters.
-
C.
Michael Rachmil
Michael Rachmil is a film producer best known for his work on the 1987 romantic comedy "Roxanne" starring Steve Martin.
-
D.
Jeremy Zuckerman
Jeremy Zuckerman is an American composer best known for his atmospheric and emotionally rich scores for the animated series "Avatar: The Last Airbender" and its sequel "The Legend of Korra."
-
E.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d971484aa08190a8adfafabe600903 |
completed | April 10, 2026, 9:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6a55daf788190be72af98b288bd70 |
completed | May 3, 2026, 1:31 a.m. |
Created at: April 9, 2026, 5:40 p.m.