Triple

T568655
Position Surface form Disambiguated ID Type / Status
Subject Berlin U-Bahn line U6 E13613 entity
Predicate hasStation P35 FINISHED
Object Scharnweberstraße
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
E72034 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: Scharnweberstraße | Statement: [Berlin U-Bahn line U6, hasStation, Scharnweberstraße]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scharnweberstraße
Context triple: [Berlin U-Bahn line U6, hasStation, Scharnweberstraße]
  • A. Holzhauser Straße
    Holzhauser Straße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • B. Otisstraße
    Otisstraße is a Berlin U-Bahn station on line U6 located in the Reinickendorf district of the city.
  • C. Bahnhofstraße
    Bahnhofstraße is a central street in Chemnitz, Germany, known for serving as the main access route to Chemnitz Hauptbahnhof, the city's primary railway station.
  • D. Brückenstraße
    Brückenstraße is a street in Chemnitz, Germany, known for being the prominent urban backdrop in front of the iconic Karl Marx Monument.
  • E. Marktstraße
    Marktstraße is the historic main street and central pedestrian thoroughfare of Bad Tölz, known for its traditional Bavarian architecture and lively shops and cafes.
  • 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: Scharnweberstraße
Triple: [Berlin U-Bahn line U6, hasStation, Scharnweberstraße]
Generated description
Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Scharnweberstraße
Target entity description: Scharnweberstraße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • A. Holzhauser Straße
    Holzhauser Straße is a station on Berlin’s U6 U-Bahn line serving the Reinickendorf district in the north of the city.
  • B. Otisstraße
    Otisstraße is a Berlin U-Bahn station on line U6 located in the Reinickendorf district of the city.
  • C. Bahnhofstraße
    Bahnhofstraße is a central street in Chemnitz, Germany, known for serving as the main access route to Chemnitz Hauptbahnhof, the city's primary railway station.
  • D. Brückenstraße
    Brückenstraße is a street in Chemnitz, Germany, known for being the prominent urban backdrop in front of the iconic Karl Marx Monument.
  • E. Marktstraße
    Marktstraße is the historic main street and central pedestrian thoroughfare of Bad Tölz, known for its traditional Bavarian architecture and lively shops and cafes.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b0406d481908af5fc7bc67103fb completed March 1, 2026, 8:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ff4a68e0819091efedcd8c620d01 completed March 2, 2026, 3:08 a.m.
NEDg Description generation batch_69a5002609648190a6726d1deb25d3a1 completed March 2, 2026, 3:12 a.m.
NED2 Entity disambiguation (via description) batch_69a5007bdf5c81908eb3f6228b39e7b0 completed March 2, 2026, 3:14 a.m.
Created at: March 1, 2026, 7:33 p.m.