Triple
T17308736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friedrichshain-Kreuzberg |
E420234
|
entity |
| Predicate | containsQuarter |
P14076
|
FINISHED |
| Object | Bergmannkiez |
E613474
|
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: Bergmannkiez | Statement: [Friedrichshain-Kreuzberg, containsQuarter, Bergmannkiez]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bergmannkiez Context triple: [Friedrichshain-Kreuzberg, containsQuarter, Bergmannkiez]
-
A.
Bergmannkiez
chosen
Bergmannkiez is a popular, lively neighborhood in Berlin known for its historic architecture, café-lined streets, and vibrant cultural scene.
-
B.
Biesenthal
Biesenthal is a small town in the Barnim district of Brandenburg, Germany, known for its surrounding lakes, forests, and location within the Barnim Nature Park.
-
C.
Henschhausen
Henschhausen is a small district or locality that forms part of the town of Bacharach in Rhineland-Palatinate, Germany.
-
D.
Marienfelde
Marienfelde is a locality in the southern part of Berlin known for its residential areas and historical refugee reception center.
-
E.
Meyenheim
Meyenheim is a commune in northeastern France that hosts a significant French military presence, including units such as the Régiment de marche du Tchad.
- 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_69d889d22b848190a4663d0b8f8f76e7 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43900eca88190930af0e4ec4fc0f9 |
completed | April 19, 2026, 2:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0180e30934819087b7c838c8874aff |
completed | May 11, 2026, 7:10 a.m. |
Created at: April 10, 2026, 5:43 a.m.