Triple

T3842371
Position Surface form Disambiguated ID Type / Status
Subject Pankow E93479 entity
Predicate knownFor P22 FINISHED
Object Prenzlauer Berg district 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 district | Statement: [Pankow, knownFor, Prenzlauer Berg district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Prenzlauer Berg district
Context triple: [Pankow, knownFor, Prenzlauer Berg district]
  • 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. Friedrichshain
    Friedrichshain is a vibrant district in Berlin known for its alternative culture, nightlife, and historic sites including remnants of the Berlin Wall.
  • 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. Berlin-Mitte locality
    Berlin-Mitte locality is a central urban district of Berlin known for its historic core, major government buildings, and many of the city’s most prominent cultural and tourist landmarks.
  • 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_69aed96ce578819084ab16e3439976c9 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69aeebb397ac81908f74a42a0eeb8682 completed March 9, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69bda3f5a8a88190a494a9338c01962a completed March 20, 2026, 7:45 p.m.
Created at: March 9, 2026, 3:18 p.m.