Triple

T16050728
Position Surface form Disambiguated ID Type / Status
Subject U-Bahn line U9 E389344 entity
Predicate hasStation P35 FINISHED
Object Birkenstraße E1113283 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: Birkenstraße | Statement: [U-Bahn line U9, hasStation, Birkenstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Birkenstraße
Context triple: [U-Bahn line U9, hasStation, Birkenstraße]
  • A. Birkenstraße chosen
    Birkenstraße is a Berlin U-Bahn station on line U9 located in the Moabit district of the city.
  • 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. Sambesistraße
    Sambesistraße is a street in Berlin’s Afrikanisches Viertel, a neighborhood known for roads named after African regions, rivers, and countries.
  • D. Hedderichstraße
    Hedderichstraße is a street in Frankfurt am Main, Germany, located in the Sachsenhausen district and connected to the city’s public transport network.
  • E. Bolkerstraße
    Bolkerstraße is a historic and lively street in Düsseldorf’s Altstadt, known for its dense concentration of bars, restaurants, and nightlife.
  • 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_6a01673979608190905afae3071413c0 completed May 11, 2026, 5:20 a.m.
Created at: April 10, 2026, 4:56 a.m.