Triple

T14123321
Position Surface form Disambiguated ID Type / Status
Subject Dorotheenstadt E339957 entity
Predicate borderedBy P224 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: [Dorotheenstadt, borderedBy, Friedrichstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friedrichstraße
Context triple: [Dorotheenstadt, borderedBy, 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. Hermannstraße
    Hermannstraße is a Berlin railway and U-Bahn station in the Neukölln district that serves as a key interchange point on the city’s Ringbahn network.
  • C. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • D. Nürnberger Straße
    Nürnberger Straße is a central Berlin street in the Schöneberg/Charlottenburg area, known for its proximity to major shopping and transport hubs like Wittenbergplatz and the Kurfürstendamm.
  • E. Maximilianstraße
    Maximilianstraße is one of Munich’s most famous boulevards, known for its luxury boutiques, grand architecture, and cultural 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6095548881908a9e66adccca92d2 completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf07feb48190b7519204b4f789b4 completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:22 p.m.