Triple
T1033464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ted Sarandos |
E22304
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ted Sarandos |
E22304
|
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: Ted Sarandos | Statement: [Ted Sarandos, name, Ted Sarandos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ted Sarandos Context triple: [Ted Sarandos, name, Ted Sarandos]
-
A.
Ted Sarandos
chosen
Ted Sarandos is an American media executive best known as the longtime chief content officer and co-CEO of Netflix, where he has overseen the company’s rise as a dominant global streaming and original content powerhouse.
-
B.
Todd Ricketts
Todd Ricketts is an American businessman and political fundraiser best known as a co-owner of the Chicago Cubs and a member of the prominent Ricketts family.
-
C.
Mark Parker
Mark Parker is an American businessman best known for serving as the longtime CEO and later executive chairman of Nike, Inc.
-
D.
Brad Treliving
Brad Treliving is a Canadian ice hockey executive known for serving as an NHL general manager, including leading the front office of the Toronto Maple Leafs.
-
E.
Thomas Grazer
Thomas Grazer is the son of acclaimed American film and television producer Brian Grazer.
- 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_69a493d848848190aed4011b34b2e8d3 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b812c9948190a37c2b1d3d32ea38 |
completed | March 1, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac3bc15a6c81909a71bf17b5cd4019 |
completed | March 7, 2026, 2:52 p.m. |
Created at: March 1, 2026, 7:41 p.m.