Triple

T16483334
Position Surface form Disambiguated ID Type / Status
Subject Kölner Eisstadion an der Lentstraße E400375 entity
Predicate locatedOnStreet P959 FINISHED
Object Lentstraße NE NERFINISHED

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: Lentstraße | Statement: [Kölner Eisstadion an der Lentstraße, locatedOnStreet, Lentstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lentstraße
Context triple: [Kölner Eisstadion an der Lentstraße, locatedOnStreet, Lentstraße]
  • A. Lentstraße chosen
    Lentstraße is a street in Cologne, Germany, known for hosting the Kölner Eisstadion ice rink.
  • 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. Lange Straße
    Lange Straße is a central street in Oldenburg, Germany, known as a main shopping thoroughfare and for landmarks such as the historic Lappan tower.
  • D. Taubenstraße
    Taubenstraße is a street in Hamburg, Germany, located in the St. Pauli district near the Reeperbahn and the Spielbudenplatz entertainment area.
  • E. Gerichtstraße
    Gerichtstraße is a street in Berlin, Germany, located in the Wedding district and known for its mix of residential buildings, commercial spaces, and cultural venues.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e0420ac81908f9a3548ddb3b1ff completed April 18, 2026, 7:08 a.m.
Created at: April 10, 2026, 5:13 a.m.