Triple

T14266187
Position Surface form Disambiguated ID Type / Status
Subject U9 E353649 entity
Predicate hasStation P35 FINISHED
Object Spichernstraße
Spichernstraße is a Berlin U-Bahn station that serves as an interchange point on the city's underground network.
 E1119448 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: Spichernstraße | Statement: [U9, hasStation, Spichernstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Spichernstraße
Context triple: [U9, hasStation, Spichernstraße]
  • A. Lothringerstraße
    Lothringerstraße is a central street in Vienna, Austria, located near major landmarks such as Karlsplatz and the Ringstrasse.
  • B. Eichhornstraße
    Eichhornstraße is a street in central Berlin, Germany, located near Leipziger Platz in the city’s historic and commercial district.
  • C. Bergmannstraße
    Bergmannstraße is a notable street in Berlin, Germany, known for its lively mix of cafés, shops, and historic sites including the Luisenstädtischer Friedhof cemetery.
  • D. 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.
  • 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: Spichernstraße
Triple: [U9, hasStation, Spichernstraße]
Generated description
Spichernstraße is a Berlin U-Bahn station that serves as an interchange point on the city's underground network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Spichernstraße
Target entity description: Spichernstraße is a Berlin U-Bahn station that serves as an interchange point on the city's underground network.
  • A. Lothringerstraße
    Lothringerstraße is a central street in Vienna, Austria, located near major landmarks such as Karlsplatz and the Ringstrasse.
  • B. Eichhornstraße
    Eichhornstraße is a street in central Berlin, Germany, located near Leipziger Platz in the city’s historic and commercial district.
  • C. Bergmannstraße
    Bergmannstraße is a notable street in Berlin, Germany, known for its lively mix of cafés, shops, and historic sites including the Luisenstädtischer Friedhof cemetery.
  • D. 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.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6358c2288190ac1fd26e688a605d completed April 14, 2026, 3:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cd12c308190ac868ffe7c5539b0 completed May 8, 2026, 4:18 p.m.
NEDg Description generation batch_69fe17fc37ec8190b2e9c786a5e7843e completed May 8, 2026, 5:06 p.m.
NED2 Entity disambiguation (via description) batch_69fe18786294819080ce5ee0d8af00c9 completed May 8, 2026, 5:08 p.m.
Created at: April 10, 2026, 1:09 a.m.