Triple
T13291885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariendorf |
E316577
|
entity |
| Predicate | adjacentTo |
P224
|
FINISHED |
| Object | Marienfelde locality |
E221065
|
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: Marienfelde locality | Statement: [Mariendorf, adjacentTo, Marienfelde locality]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marienfelde locality Context triple: [Mariendorf, adjacentTo, Marienfelde locality]
-
A.
Marienfelde
chosen
Marienfelde is a locality in the southern part of Berlin known for its residential areas and historical refugee reception center.
-
B.
Neu-Hohenschönhausen locality
Neu-Hohenschönhausen is a residential locality in the northeast of Berlin, Germany, known for its large prefabricated housing estates built during the GDR era.
-
C.
Alt-Mariendorf
Alt-Mariendorf is a Berlin U-Bahn station in the Mariendorf district that serves as the southern terminus of line U6.
-
D.
Nittendorf
Nittendorf is a municipality in the Upper Palatinate region of Bavaria, Germany, situated west of the city of Regensburg.
-
E.
Ludwigsfelde
Ludwigsfelde is a town in the German state of Brandenburg, located just south of Berlin and known for its industrial history and automotive manufacturing.
- 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_69d806b349908190a9a61dd9323bf153 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99077a8f48190b1163448a3a978a2 |
completed | April 11, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f716d6dc988190ab7183089113237f |
completed | May 3, 2026, 9:35 a.m. |
Created at: April 9, 2026, 9:27 p.m.