Triple
T7182168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gordon Bowker |
E167473
|
entity |
| Predicate | businessPartner |
P282
|
FINISHED |
| Object | Zev Siegl |
E107329
|
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: Zev Siegl | Statement: [Gordon Bowker, businessPartner, Zev Siegl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zev Siegl Context triple: [Gordon Bowker, businessPartner, Zev Siegl]
-
A.
Zev Siegl
chosen
Zev Siegl is an American entrepreneur and co-founder of the Starbucks coffee company.
-
B.
Adam Siegel
Adam Siegel is a film producer known for his work on action and genre movies, including the 2008 thriller "Wanted."
-
C.
Sam Zussman
Sam Zussman is a sports and media executive who serves as a top business leader for the NBA’s Brooklyn Nets organization.
-
D.
Zeek Braverman
Zeek Braverman is a central patriarchal character on the television drama "Parenthood," known for his gruff warmth, traditional values, and complex relationships with his adult children and grandchildren.
-
E.
Uriel Frisch
Uriel Frisch is a French physicist and mathematician renowned for his contributions to fluid dynamics and turbulence theory.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e8bc25088190a7d7f3ba2461b5e9 |
completed | March 27, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7bf8d76ac8190a2e29f2650e7af28 |
completed | March 28, 2026, 11:46 a.m. |
Created at: March 27, 2026, 2:49 p.m.