Triple
T15252805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Ballhaus |
E364560
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Michael Ballhaus |
E364560
|
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: Michael Ballhaus | Statement: [Michael Ballhaus, name, Michael Ballhaus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Ballhaus Context triple: [Michael Ballhaus, name, Michael Ballhaus]
-
A.
Michael Ballhaus
chosen
Michael Ballhaus was a renowned German cinematographer celebrated for his dynamic camera work and frequent collaborations with director Martin Scorsese.
-
B.
Paul Weinert
Paul Weinert was a United States Army soldier and Medal of Honor recipient recognized for his bravery during the Indian Wars.
-
C.
Michael Bollner
Michael Bollner is a German former child actor best known for playing Augustus Gloop in the 1971 film "Willy Wonka & the Chocolate Factory."
-
D.
Paul Zimmerer
Paul Zimmerer was an American entrepreneur best known as the founder of Lindsay Corporation, a major manufacturer of agricultural irrigation and infrastructure equipment.
-
E.
Paul Biegler
Paul Biegler is a small-town Michigan lawyer and the central protagonist of the courtroom drama novel and film "Anatomy of a Murder."
- 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007f728648190b2c86e4528542b65 |
completed | April 15, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180bd1e5c8190a6a96581ce8a37de |
completed | May 11, 2026, 7:09 a.m. |
Created at: April 10, 2026, 3:13 a.m.