Triple
T3690680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oberhavel |
E78334
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Hohen Neuendorf |
E392707
|
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: Hohen Neuendorf | Statement: [Oberhavel, hasMunicipality, Hohen Neuendorf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hohen Neuendorf Context triple: [Oberhavel, hasMunicipality, Hohen Neuendorf]
-
A.
Hohen Neuendorf
chosen
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.
-
B.
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.
-
C.
Fürstenwalde
Fürstenwalde is a town in eastern Germany’s Brandenburg region, known for its location on the River Spree and its historic churches and medieval architecture.
-
D.
Hasselwerder
Hasselwerder is a small island located in Lake Tegel in Berlin, Germany.
-
E.
Langendorf
Langendorf is a municipality in the canton of Solothurn in northwestern Switzerland.
- 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_69b5282613d0819085a47d1fffdaa4d5 |
completed | March 14, 2026, 9:19 a.m. |
Created at: March 8, 2026, 3:26 p.m.