Triple
T7813630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schönefeld |
E180745
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Königs Wusterhausen |
E598785
|
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: Königs Wusterhausen | Statement: [Schönefeld, borderedBy, Königs Wusterhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Königs Wusterhausen Context triple: [Schönefeld, borderedBy, Königs Wusterhausen]
-
A.
Königs Wusterhausen
chosen
Königs Wusterhausen is a town in the German state of Brandenburg, located southeast of Berlin and integrated into the capital’s commuter belt.
-
B.
Schönhausen
Schönhausen is a village in Saxony-Anhalt, Germany, best known as the birthplace of 19th-century statesman Otto von Bismarck.
-
C.
Hohen Neuendorf
Hohen Neuendorf is a town in the German state of Brandenburg, located just north of Berlin and known as a residential suburb with access to the capital.
-
D.
Schorfheide
Schorfheide is a large forested and lake-rich area in Brandenburg, Germany, known for its protected natural landscapes and historical use as a royal and political hunting ground.
-
E.
Zossen
Zossen is a town in Brandenburg, Germany, historically notable as a major military command center, including serving as a key headquarters area during the Soviet occupation after 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78f3d6481909841d64117f657e1 |
completed | March 30, 2026, 10:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cbded6d1a881909d9816fcd8a55e49 |
completed | March 31, 2026, 2:48 p.m. |
Created at: March 30, 2026, 4:38 p.m.