Triple

T5702004
Position Surface form Disambiguated ID Type / Status
Subject Museumstrasse station area E125685 entity
Predicate adjacentTo P224 FINISHED
Object Museumstrasse E542984 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: Museumstrasse | Statement: [Museumstrasse station area, adjacentTo, Museumstrasse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Museumstrasse
Context triple: [Museumstrasse station area, adjacentTo, Museumstrasse]
  • A. Museumstrasse chosen
    Museumstrasse is a street that lends its name to the surrounding station area, likely serving as a notable local thoroughfare or landmark.
  • B. Paradestraße
    Paradestraße is a Berlin U-Bahn station on the north–south route in the Tempelhof-Schöneberg district, known for serving the U6 line.
  • C. Chausseestraße
    Chausseestraße is a major historic street in Berlin, Germany, known for its cultural landmarks and central location.
  • D. Prinzenstraße
    Prinzenstraße is a Berlin U-Bahn station on line U1 located in the Kreuzberg district.
  • E. Kaufingerstraße
    Kaufingerstraße is one of Munich’s main and oldest pedestrian shopping streets, lined with stores and historic buildings in the city center.
  • 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_69c0082c96988190b3a6a201edce472a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0245581988190a819b8137533ed31 completed March 22, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c097e576a481909b918bfc93082fa9 completed March 23, 2026, 1:31 a.m.
Created at: March 22, 2026, 3:45 p.m.