Triple
T19206080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Armin B. Cremers |
E480236
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Armin B. Cremers |
—
|
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: Armin B. Cremers | Statement: [Armin B. Cremers, name, Armin B. Cremers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Armin B. Cremers Context triple: [Armin B. Cremers, name, Armin B. Cremers]
-
A.
Armin B. Cremers
chosen
Armin B. Cremers is a German computer scientist known for his contributions to artificial intelligence, robotics, and information systems, and for mentoring influential researchers in these fields.
-
B.
Robert Brinkmann
Robert Brinkmann is a German-born cinematographer known for his work on feature films, music-related projects, and television.
-
C.
Michael Lehmann
Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
-
D.
Markus J. Pflaum
Markus J. Pflaum is a German mathematician recognized for his significant contributions to differential geometry and related fields, for which he received the Carl Friedrich Gauss Prize.
-
E.
Martin Benrath
Martin Benrath was a German actor known for his extensive work in film, television, and theater from the mid-20th century onward.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5f99d8ad0819098ebd4ee007149f1 |
completed | April 20, 2026, 10:02 a.m. |
Created at: April 10, 2026, 1:19 p.m.