Triple
T3690663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberhavel |
E78334
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Havelland |
E242434
|
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: Havelland | Statement: [Oberhavel, borders, Havelland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Havelland Context triple: [Oberhavel, borders, 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.
Münsterland
Münsterland is a rural region in northwestern Germany known for its historic castles, cycling routes, and traditional Westphalian culture.
-
D.
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.
-
E.
Wendland region
The Wendland region is a rural area in the eastern part of Lower Saxony, Germany, known for its historic Rundling (circular) villages and strong environmental and anti-nuclear activism.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e6147c8190ae358e8cc94f479c |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3c9e9c08190bd97642ccf39b172 |
completed | March 14, 2026, 2:11 a.m. |
Created at: March 8, 2026, 3:26 p.m.