Triple
T10333676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Altmark |
E242941
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | town of Osterburg |
E598779
|
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: town of Osterburg | Statement: [Altmark, contains, town of Osterburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: town of Osterburg Context triple: [Altmark, contains, town of Osterburg]
-
A.
Osterburg
chosen
Osterburg is a small town in the German state of Saxony-Anhalt, known for its historic architecture and rural surroundings.
-
B.
Burgstädt
Burgstädt is a small town in the German state of Saxony, known for its traditional architecture and location near the city of Chemnitz.
-
C.
Rummelsburg
Rummelsburg is a locality in the Berlin borough of Lichtenberg, known for its lakeside setting along the Rummelsburger See and a mix of industrial heritage and newer residential developments.
-
D.
Marktoberdorf
Marktoberdorf is a small Bavarian town in southern Germany known as an administrative and cultural center in the Allgäu region.
-
E.
Bergneustadt
Bergneustadt is a small town in North Rhine-Westphalia, Germany, known for its location in the hilly Oberbergischer Kreis region and its traditional half-timbered architecture.
- 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_69d381af787481908bc401325c760a88 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4dfc366b481909c49f199892e9d42 |
completed | April 7, 2026, 10:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d75054515081908240f985f8b6e2df |
completed | April 9, 2026, 7:08 a.m. |
Created at: April 6, 2026, 11:53 a.m.