Triple

T15735799
Position Surface form Disambiguated ID Type / Status
Subject Schulstraße (Berlin) E381466 entity
Predicate hasNearbyPlace P3449 FINISHED
Object Müllerstraße (Berlin) E376992 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: Müllerstraße (Berlin) | Statement: [Schulstraße (Berlin), hasNearbyPlace, Müllerstraße (Berlin)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Müllerstraße (Berlin)
Context triple: [Schulstraße (Berlin), hasNearbyPlace, Müllerstraße (Berlin)]
  • A. Müllerstraße chosen
    Müllerstraße is a major thoroughfare in Berlin’s Wedding district, known for its dense urban character, shops, and public transport connections.
  • B. Amrumer Straße
    Amrumer Straße is a Berlin U-Bahn station on the U9 line located in the Wedding district of the city.
  • C. Reinickendorfer Straße
    Reinickendorfer Straße is a Berlin U-Bahn station on line U6 located in the central district of Mitte.
  • D. Michaelerstraße
    Michaelerstraße is a historic street in central Vienna, Austria, forming part of the old city’s prestigious area near the Hofburg Palace.
  • E. Kröpeliner Straße
    Kröpeliner Straße is a major pedestrian shopping street in the historic center of Rostock, Germany, known for its shops, cafés, and role as a central venue for city events.
  • 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_69d86d9cdb648190bf3171be0bd7d872 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04fd586a88190aa1b1b88368d386f completed April 16, 2026, 2:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8300a4248190ba52573b57f31b36 completed May 9, 2026, 6:54 p.m.
Created at: April 10, 2026, 4:46 a.m.