Triple
T6092101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Bewkes |
E135789
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bewkes |
E135789
|
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: Bewkes | Statement: [Jeff Bewkes, familyName, Bewkes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bewkes Context triple: [Jeff Bewkes, familyName, Bewkes]
-
A.
Bewkes
chosen
Bewkes is the surname of Jeff Bewkes, the American media executive best known for serving as CEO of Time Warner.
-
B.
Gilbert Adler
Gilbert Adler is an American film and television producer known for his work on genre projects including horror and superhero adaptations.
-
C.
Garfinkle
Garfinkle is the original surname of American actor John Garfield, a prominent film star of the 1930s and 1940s known for his intense, naturalistic performances.
-
D.
Bitty Schram
Bitty Schram is an American actress best known for playing Sharona Fleming, Adrian Monk’s original assistant, on the television series "Monk."
-
E.
Jay Witmark
Jay Witmark was a music publisher best known as one of the founders of the influential American music publishing firm M. Witmark & Sons.
- 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057ab7324819086d4708e6f9391c0 |
completed | March 22, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c125365a7481909e40d01c2d3590aa |
completed | March 23, 2026, 11:34 a.m. |
Created at: March 22, 2026, 4:12 p.m.