Triple

T13676417
Position Surface form Disambiguated ID Type / Status
Subject Chausseestraße E327889 entity
Predicate connects P390 FINISHED
Object Brunnenstraße E1033959 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: Brunnenstraße | Statement: [Chausseestraße, connects, Brunnenstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brunnenstraße
Context triple: [Chausseestraße, connects, Brunnenstraße]
  • A. Brunnenstraße chosen
    Brunnenstraße is a major street in Berlin, Germany, running through the districts of Mitte and Gesundbrunnen and known for its mix of historic buildings, shops, and cultural venues.
  • B. Beusselstraße
    Beusselstraße is a railway station in Berlin that serves the city's circular Ringbahn line and connects the surrounding Moabit area to the wider S-Bahn network.
  • C. Grunerstraße
    Grunerstraße is a central street in Berlin located near Alexanderplatz, known for carrying heavy traffic through the city’s Mitte district.
  • D. Hermannstraße
    Hermannstraße is a Berlin railway and U-Bahn station in the Neukölln district that serves as a key interchange point on the city’s Ringbahn network.
  • E. Hedderichstraße
    Hedderichstraße is a street in Frankfurt am Main, Germany, located in the Sachsenhausen district and connected to the city’s public transport network.
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc65c04988190b675e6fb7241e53c completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8cae6f081908145b6cd4c0ba53c completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 9:53 p.m.