Triple

T16050729
Position Surface form Disambiguated ID Type / Status
Subject U-Bahn line U9 E389344 entity
Predicate hasStation P35 FINISHED
Object Turmstraße E614911 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: Turmstraße | Statement: [U-Bahn line U9, hasStation, Turmstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Turmstraße
Context triple: [U-Bahn line U9, hasStation, Turmstraße]
  • A. Turmstraße chosen
    Turmstraße is a major street and local center in Berlin’s Moabit district, known for its shops, eateries, and public transport connections.
  • B. Burgstraße
    Burgstraße is a historic street located in the Old Town (Altstadt) of Hanover, Germany, known for its traditional architecture and central location.
  • C. Bräunerstraße
    Bräunerstraße is a street in Vienna’s historic city center, known for its upscale shops, historic buildings, and proximity to major landmarks such as the Graben.
  • D. Taubenstraße
    Taubenstraße is a street in Hamburg, Germany, located in the St. Pauli district near the Reeperbahn and the Spielbudenplatz entertainment area.
  • E. Burgenstraße
    Burgenstraße is a famous German tourist route known for connecting numerous historic castles and picturesque medieval towns.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18361c31481908b253e8b814ec9f6 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170db6c6881908f5670c8282f4097 completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 4:56 a.m.