Triple
T14295409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Berlin |
E354425
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Prenzlauer Berg |
E447971
|
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: Prenzlauer Berg | Statement: [Northern Berlin, hasPart, Prenzlauer Berg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prenzlauer Berg Context triple: [Northern Berlin, hasPart, Prenzlauer Berg]
-
A.
Prenzlauer Berg
chosen
Prenzlauer Berg is a trendy, gentrified district in Berlin known for its historic architecture, vibrant café culture, and popular nightlife.
-
B.
Friedrichshain-Kreuzberg
Friedrichshain-Kreuzberg is a central Berlin borough known for its vibrant nightlife, alternative culture, and diverse, historically rich neighborhoods.
-
C.
Kreuzberg
Kreuzberg is a prominent mountain in the Rhön range of central Germany, known for its monastery, pilgrimage site, and scenic hiking opportunities.
-
D.
Kreuzberg
Kreuzberg is a vibrant, historically working-class district in central Berlin known for its multicultural community, alternative culture, and lively arts and nightlife scenes.
-
E.
Friedrichshain
Friedrichshain is a vibrant district in Berlin known for its alternative culture, nightlife, and historic sites including remnants of the Berlin Wall.
- 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_69fe7e7563188190b50c4413cd5dde37 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 1:11 a.m.