Triple
T11584003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clerks |
E274703
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | David Klein |
E772262
|
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: David Klein | Statement: [Clerks, cinematographyBy, David Klein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Klein Context triple: [Clerks, cinematographyBy, David Klein]
-
A.
David Klein
chosen
David Klein is an American cinematographer best known for his frequent collaborations with filmmaker Kevin Smith and his work on independent films and television series.
-
B.
Jonathan Klein
Jonathan Klein is a British businessman best known as the co-founder and longtime leader of the global stock photography and media company Getty Images.
-
C.
Dan Klein
Dan Klein is a prominent computer scientist and professor at UC Berkeley known for his influential research in natural language processing and machine learning.
-
D.
Michael Klein
Michael Klein is the father of Canadian author and activist Naomi Klein.
-
E.
Chris Klein
Chris Klein is a former American professional soccer player who later became a sports executive, notably serving as president of Major League Soccer’s LA Galaxy.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8904db5748190ae5f10ae86ccdf46 |
completed | April 10, 2026, 5:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e3185fc81908c1b838e6883de2f |
completed | May 2, 2026, 3:54 p.m. |
Created at: April 8, 2026, 9:38 p.m.