Triple
T20898390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloodline |
E514603
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | Daniel Zelman |
—
|
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: Daniel Zelman | Statement: [Bloodline, creator, Daniel Zelman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Zelman Context triple: [Bloodline, creator, Daniel Zelman]
-
A.
Daniel Zelman
chosen
Daniel Zelman is an American actor, screenwriter, and television producer known for co-creating the legal thriller series "Damages."
-
B.
Jonathan Zalben
Jonathan Zalben is a film and television composer known for scoring a variety of independent features and documentaries.
-
C.
David Zabel
David Zabel is an American television writer and producer best known for his work as a showrunner and executive producer on the long-running medical drama "ER."
-
D.
Dave Zeltserman
Dave Zeltserman is an American crime and mystery novelist known for his dark, hardboiled style and critically acclaimed noir fiction.
-
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 (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_69e0b4f7ebe48190952a85547a0f31a1 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8f826788190b11008cc94b2a4e4 |
completed | April 21, 2026, 3:03 a.m. |
Created at: April 16, 2026, 12:47 p.m.