Triple

T16246528
Position Surface form Disambiguated ID Type / Status
Subject Bahnhofsviertel E394383 entity
Predicate hasLandmark P105 FINISHED
Object Niddastraße
Niddastraße is a street in Frankfurt’s Bahnhofsviertel district known for its mix of nightlife, residential buildings, and diverse urban culture.
 E1298791 NE FINISHED

How this triple was built (4 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: Niddastraße | Statement: [Bahnhofsviertel, hasLandmark, Niddastraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Niddastraße
Context triple: [Bahnhofsviertel, hasLandmark, Niddastraße]
  • A. Treitlstraße
    Treitlstraße is a street in central Vienna, Austria, located near Karlsplatz and the Vienna University of Technology.
  • B. Sambesistraße
    Sambesistraße is a street in Berlin’s Afrikanisches Viertel, a neighborhood known for roads named after African regions, rivers, and countries.
  • C. Taubenstraße
    Taubenstraße is a street in Hamburg, Germany, located in the St. Pauli district near the Reeperbahn and the Spielbudenplatz entertainment area.
  • D. Rosenbergstraße
    Rosenbergstraße is a street that lends its name to and hosts the Rosenbergstraße campus.
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Niddastraße
Triple: [Bahnhofsviertel, hasLandmark, Niddastraße]
Generated description
Niddastraße is a street in Frankfurt’s Bahnhofsviertel district known for its mix of nightlife, residential buildings, and diverse urban culture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Niddastraße
Target entity description: Niddastraße is a street in Frankfurt’s Bahnhofsviertel district known for its mix of nightlife, residential buildings, and diverse urban culture.
  • A. Treitlstraße
    Treitlstraße is a street in central Vienna, Austria, located near Karlsplatz and the Vienna University of Technology.
  • B. Sambesistraße
    Sambesistraße is a street in Berlin’s Afrikanisches Viertel, a neighborhood known for roads named after African regions, rivers, and countries.
  • C. Taubenstraße
    Taubenstraße is a street in Hamburg, Germany, located in the St. Pauli district near the Reeperbahn and the Spielbudenplatz entertainment area.
  • D. Rosenbergstraße
    Rosenbergstraße is a street that lends its name to and hosts the Rosenbergstraße campus.
  • E. 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.
  • F. None of above. chosen

Provenance (5 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_69d87f2171208190951025e526947816 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245931074819096f38003da70f271 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a032ff689cc81908f4944b8917ebe28 completed May 12, 2026, 1:49 p.m.
NEDg Description generation batch_6a0331d2b1ec81908fdd6278a4e378a4 completed May 12, 2026, 1:57 p.m.
NED2 Entity disambiguation (via description) batch_6a03329ea1b08190b5922485cbee83a8 completed May 12, 2026, 2:01 p.m.
Created at: April 10, 2026, 5:04 a.m.