Triple

T18381550
Position Surface form Disambiguated ID Type / Status
Subject Seckbacher Landstraße E446460 entity
Predicate hasStreetAccess P959 FINISHED
Object Seckbacher Landstraße 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: Seckbacher Landstraße | Statement: [Seckbacher Landstraße, hasStreetAccess, Seckbacher Landstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seckbacher Landstraße
Context triple: [Seckbacher Landstraße, hasStreetAccess, Seckbacher Landstraße]
  • A. Seckbacher Landstraße chosen
    Seckbacher Landstraße is a public transport stop in the Bornheim district of Frankfurt am Main, Germany.
  • B. Karmarschstraße
    Karmarschstraße is a central shopping and traffic street in Hanover, Germany, running through the city center near Kröpcke square.
  • C. Brienner Straße
    Brienner Straße is a historic boulevard in Munich, Germany, known for its neoclassical architecture and its role as one of the city’s grand royal avenues.
  • D. Wipplingerstraße
    Wipplingerstraße is a historic street in Vienna’s city center known for its proximity to major squares, financial institutions, and notable civic buildings.
  • E. Scharnweberstraße
    Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • 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_69d8b9f370b88190b1e5081c2c238e7f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e5179b60f88190adf39e85375bd11b completed April 19, 2026, 5:57 p.m.
Created at: April 10, 2026, 10:45 a.m.