Triple
T20387319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cowboy Bebop (2021 TV series) |
E497991
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jeff Pinkner |
—
|
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: Jeff Pinkner | Statement: [Cowboy Bebop (2021 TV series), executiveProducer, Jeff Pinkner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Pinkner Context triple: [Cowboy Bebop (2021 TV series), executiveProducer, Jeff Pinkner]
-
A.
Jeff Pinkner
chosen
Jeff Pinkner is an American television writer and producer known for his work on series such as "Fringe," "Alias," and "Lost."
-
B.
Jonathan Stern
Jonathan Stern is an American film and television producer best known for his work on offbeat comedies such as "Wet Hot American Summer" and various projects for Adult Swim and streaming platforms.
-
C.
Scott Pinsker
Scott Pinsker is an American author, filmmaker, and media commentator known for his work on politics, branding, and culture.
-
D.
Dan Bucatinsky
Dan Bucatinsky is an American actor, writer, and producer best known for his Emmy-winning role on "Scandal" and his work in television comedy and drama.
-
E.
Mark Pinsker
Mark Pinsker is a mathematician best known for his contributions to information theory, particularly the development of Pinsker's inequality.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790c935881908f901d058e6a83a9 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.