Triple

T16198549
Position Surface form Disambiguated ID Type / Status
Subject Prinzenstraße E393134 entity
Predicate locatedIn P40 FINISHED
Object Kreuzberg E153187 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: Kreuzberg | Statement: [Prinzenstraße, locatedIn, Kreuzberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kreuzberg
Context triple: [Prinzenstraße, locatedIn, Kreuzberg]
  • A. Kreuzberg chosen
    Kreuzberg is a vibrant, historically working-class district in central Berlin known for its multicultural community, alternative culture, and lively arts and nightlife scenes.
  • B. Kreuzberg
    Kreuzberg is a prominent mountain in the Rhön range of central Germany, known for its monastery, pilgrimage site, and scenic hiking opportunities.
  • C. Prenzlauer Berg
    Prenzlauer Berg is a trendy, gentrified district in Berlin known for its historic architecture, vibrant café culture, and popular nightlife.
  • D. Friedrichshain-Kreuzberg
    Friedrichshain-Kreuzberg is a central Berlin borough known for its vibrant nightlife, alternative culture, and diverse, historically rich neighborhoods.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222dc6b1c8190a3d8a6451ed8b95a completed April 17, 2026, 12:09 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c28f43988190aa06da8c356b9646 completed May 10, 2026, 5:38 p.m.
Created at: April 10, 2026, 5:03 a.m.