Triple

T6110987
Position Surface form Disambiguated ID Type / Status
Subject Checkpoint Charlie E136237 entity
Predicate locatedIn P40 FINISHED
Object Friedrichstraße E73425 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: Friedrichstraße | Statement: [Checkpoint Charlie, locatedIn, Friedrichstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friedrichstraße
Context triple: [Checkpoint Charlie, locatedIn, Friedrichstraße]
  • A. Friedrichstraße chosen
    Friedrichstraße is a major central Berlin transport hub and historic thoroughfare known for its shopping, cultural venues, and role as a former border crossing during the Cold War.
  • B. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • C. Leipziger Straße
    Leipziger Straße is a major shopping and commercial street in Frankfurt’s Bockenheim district, known for its dense mix of retail, services, and local urban life.
  • D. Leipziger Straße
    Leipziger Straße is a major historic thoroughfare in central Berlin, known for its government buildings, commercial centers, and role in the city’s urban core.
  • E. Eisenacher Straße
    Eisenacher Straße is a street in Berlin’s Akazienkiez neighborhood, known for its mix of residential buildings, local shops, and cafés in the Schöneberg district.
  • 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_69c0089ea6f88190b349be53e04b4f5f completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05bbbbea88190b889a7c30af1d71a completed March 22, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640a09c60819087f3dad6d6ac6833 completed March 27, 2026, 8:32 a.m.
Created at: March 22, 2026, 4:13 p.m.