Triple
T20459289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DE40 (Brandenburg) |
E501879
|
entity |
| Predicate | containsMunicipality |
P852
|
FINISHED |
| Object | Rathenow |
—
|
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: Rathenow | Statement: [DE40 (Brandenburg), containsMunicipality, Rathenow]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rathenow Context triple: [DE40 (Brandenburg), containsMunicipality, Rathenow]
-
A.
Rathenow
chosen
Rathenow is a town in the state of Brandenburg in northeastern Germany, known historically for its optical industry.
-
B.
Sangerhausen
Sangerhausen is a town in the German state of Saxony-Anhalt, known for its historic mining heritage and its renowned Europa-Rosarium rose garden.
-
C.
Sondershausen
Sondershausen is a small town in the German state of Thuringia, known for its historic castle, former role as a princely residence, and long tradition of mining and music.
-
D.
Querfurt
Querfurt is a small historic town in the German state of Saxony-Anhalt, known for its well-preserved medieval castle and old town.
-
E.
Uelzen
Uelzen is a small town in Lower Saxony, Germany, known for its distinctive Hundertwasser-designed railway station and its role as a regional transport hub.
- 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_69e0b4ad4940819098cf2ff6413574e5 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e696a4652c8190acf79fa2e285e436 |
completed | April 20, 2026, 9:12 p.m. |
Created at: April 16, 2026, 11:33 a.m.