Triple
T14295418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Berlin |
E354425
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Märkisches Viertel |
E392708
|
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: Märkisches Viertel | Statement: [Northern Berlin, hasPart, Märkisches Viertel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Märkisches Viertel Context triple: [Northern Berlin, hasPart, Märkisches Viertel]
-
A.
Märkisches Viertel
chosen
Märkisches Viertel is a large post-war housing estate and residential district in the Reinickendorf borough of Berlin, known for its high-rise apartment blocks and dense urban layout.
-
B.
Brandenburgisches Viertel
Brandenburgisches Viertel is a residential district of the town of Eberswalde in the German state of Brandenburg.
-
C.
Bohnenviertel
Bohnenviertel is a historic quarter in central Stuttgart known for its narrow streets, traditional houses, and vibrant mix of small shops, bars, and restaurants.
-
D.
Dorotheenstadt
Dorotheenstadt is a historic district in central Berlin, Germany, known for its cultural significance and notable institutions.
-
E.
Kreuzberg
Kreuzberg is a prominent mountain in the Rhön range of central Germany, known for its monastery, pilgrimage site, and scenic hiking opportunities.
- 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_69d8278e17088190b328c5a9d4be74ff |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de717b35ec81908968994e65737c66 |
completed | April 14, 2026, 4:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdfb73334c8190a96a92d199c3b101 |
completed | May 8, 2026, 3:04 p.m. |
Created at: April 10, 2026, 1:11 a.m.