Triple
T20459150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Brandenburg |
E501876
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Havelland |
—
|
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: Havelland | Statement: [Mark Brandenburg, contains, Havelland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Havelland Context triple: [Mark Brandenburg, contains, Havelland]
-
A.
Havelland
chosen
Havelland is a rural district in western Brandenburg, Germany, known for its river landscapes along the Havel, historic towns, and agricultural character.
-
B.
Emsland
Emsland is a rural region in western Germany known for its agriculture, peatlands, and location along the River Ems near the Dutch border.
-
C.
Havelte region
The Havelte region is a rural area in the Dutch province of Drenthe known for its heathlands, prehistoric dolmens (hunebedden), and characteristic village landscapes.
-
D.
Münsterland
Münsterland is a rural region in northwestern Germany known for its historic castles, cycling routes, and traditional Westphalian culture.
-
E.
Uckermark
Uckermark is a rural historical region in northeastern Germany, known for its lakes, forests, and low population density, located primarily in the state of Brandenburg.
- 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.