Triple

T17298037
Position Surface form Disambiguated ID Type / Status
Subject former Anhalter Bahnhof E419962 entity
Predicate near P350 FINISHED
Object Stresemannstraße 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: Stresemannstraße | Statement: [former Anhalter Bahnhof, near, Stresemannstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stresemannstraße
Context triple: [former Anhalter Bahnhof, near, Stresemannstraße]
  • A. Niederkirchnerstraße chosen
    Niederkirchnerstraße is a street in central Berlin, Germany, historically associated with Nazi-era government and security offices and now home to memorial sites such as the Topography of Terror.
  • B. Reichenhainer Straße
    Reichenhainer Straße is a major street in Chemnitz, Germany, known for serving as a primary access route to the local university campus and surrounding facilities.
  • C. Karmarschstraße
    Karmarschstraße is a central shopping and traffic street in Hanover, Germany, running through the city center near Kröpcke square.
  • 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. Yorckstraße
    Yorckstraße is a major street and transport corridor in Berlin’s Kreuzberg and Schöneberg districts, known for its multiple S-Bahn stations and proximity to several historic cemeteries and railway viaducts.
  • 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e438f82788819088ea796850552297 completed April 19, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:41 a.m.