Triple

T22425215
Position Surface form Disambiguated ID Type / Status
Subject Rixdorf E554349 entity
Predicate locatedNear P294 FINISHED
Object Karl-Marx-Straße 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: Karl-Marx-Straße | Statement: [Rixdorf, locatedNear, Karl-Marx-Straße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Karl-Marx-Straße
Context triple: [Rixdorf, locatedNear, Karl-Marx-Straße]
  • A. Karl-Marx-Straße chosen
    Karl-Marx-Straße is a major commercial and residential thoroughfare in Berlin’s Neukölln district, known for its dense shops, multicultural atmosphere, and heavy traffic.
  • B. Karl-Liebknecht-Straße
    Karl-Liebknecht-Straße is a major thoroughfare in central Berlin that runs through the historic city center near Alexanderplatz and several notable landmarks.
  • C. Karl-Marx-Allee
    Karl-Marx-Allee is a monumental socialist boulevard in Berlin, known for its grand Stalinist architecture and historic role as a showcase of East German urban planning.
  • D. Leopoldstraße
    Leopoldstraße is a major boulevard in Munich known for its vibrant cafés, shops, and cultural life, especially in the Schwabing district.
  • E. Kantstraße
    Kantstraße is a major street in Berlin’s Charlottenburg district, known for its vibrant mix of shops, restaurants, 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_69e11e4f2d0c819091aa3558ea2ee630 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15a2c47bc81908b8265d83fa6fb65 completed April 29, 2026, 1:09 a.m.
Created at: April 16, 2026, 8:47 p.m.