Triple
T21524413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Proof (film) |
E531056
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Alwin H. Küchler |
—
|
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: Alwin H. Küchler | Statement: [Proof (film), cinematographyBy, Alwin H. Küchler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alwin H. Küchler Context triple: [Proof (film), cinematographyBy, Alwin H. Küchler]
-
A.
Alwin H. Küchler
chosen
Alwin H. Küchler is a German cinematographer known for his visually distinctive work on films such as "Sunshine," "Hanna," and "Steve Jobs."
-
B.
Alwin C. Ernst
Alwin C. Ernst was an American accountant and entrepreneur best known as a co-founder of the global professional services firm Ernst & Young.
-
C.
Oswald H. Ernst
Oswald H. Ernst was a U.S. Army engineer and military officer known for his service in major engineering projects and advisory roles, including work related to the Panama Canal.
-
D.
Philip J. Suess
Philip J. Suess is an American politician who serves as the mayor of Wheaton, Illinois.
-
E.
Frank P. Keller
Frank P. Keller is a film editor best known for his Academy Award-winning work on the 1968 action film "Bullitt."
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee884f4504819086bd632e62f02f58 |
completed | April 26, 2026, 9:49 p.m. |
Created at: April 16, 2026, 6:26 p.m.