Triple
T12454230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bangert, Jansen, Scholz, Schultes group |
E297613
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Bangert |
E297611
|
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: Bangert | Statement: [Bangert, Jansen, Scholz, Schultes group, namedAfter, Bangert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bangert Context triple: [Bangert, Jansen, Scholz, Schultes group, namedAfter, Bangert]
-
A.
Bangert
chosen
Bangert is a surname of German origin associated with several individuals, including those named Jansen, Scholz, and Schultes.
-
B.
Barten
Barten is the former German name of the town now known as Barciany, located in northern Poland.
-
C.
Burglauer
Burglauer is a small municipality in the Rhön-Grabfeld district of northern Bavaria, Germany.
-
D.
Rattenberg
Rattenberg is a small municipality in the Straubing-Bogen district of Lower Bavaria, Germany, known for its rural setting and traditional Bavarian character.
-
E.
Bonte
Bonte is a German surname most notably borne by Friedrich Bonte, a Kriegsmarine officer during World War II.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94da0b5988190b9df26dd3bb87337 |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f190c788190adceaab8117d52a6 |
completed | May 2, 2026, 6:14 p.m. |
Created at: April 8, 2026, 9:56 p.m.