Triple

T7517077
Position Surface form Disambiguated ID Type / Status
Subject Theater am Schiffbauerdamm E177672 entity
Predicate locatedNear P294 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: [Theater am Schiffbauerdamm, locatedNear, Friedrichstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friedrichstraße
Context triple: [Theater am Schiffbauerdamm, locatedNear, 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. 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.
  • E. 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.
  • 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_69c69f2891148190a484f3b8222c6f1b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f5f6ccc8819080ffd123fdd59a50 completed March 27, 2026, 9:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c861438bb08190a5254ed7f28aec32 completed March 28, 2026, 11:16 p.m.
Created at: March 27, 2026, 3:46 p.m.