Triple
T17787078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Otto Steinbrinck |
E444044
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Flick concern |
E1287318
|
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: Flick concern | Statement: [Otto Steinbrinck, employer, Flick concern]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Flick concern Context triple: [Otto Steinbrinck, employer, Flick concern]
-
A.
Flick concern
chosen
Flick concern was a major German industrial conglomerate built by Friedrich Flick, known for its extensive holdings in steel, coal, and armaments, particularly during the Nazi era.
-
B.
Flick
Flick is a German football manager and former player best known for coaching the German national team and leading Bayern Munich to a historic sextuple in 2020.
-
C.
Flick
Flick is a German surname most notably associated with the industrialist family behind the Flick conglomerate and the mid-20th-century Flick political and financial scandals.
-
D.
Flick
Flick is one of the basic movement actions in Laban effort theory, characterized by quick, light, and sudden motion.
-
E.
The Flick
The Flick is a Pulitzer Prize–winning play by Annie Baker that portrays the lives of three underpaid employees working in a run-down Massachusetts movie theater.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e487938418819096016ad717b014e6 |
completed | April 19, 2026, 7:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a02f835db9481909d314c17a7c59952 |
completed | May 12, 2026, 9:51 a.m. |
Created at: April 10, 2026, 10:12 a.m.