Triple

T4060844
Position Surface form Disambiguated ID Type / Status
Subject Berlin U-Bahn line U7 E86206 entity
Predicate terminus P388 FINISHED
Object Rudow
Rudow is a district in the southeastern part of Berlin, Germany, known for its residential character and connection to the city's U-Bahn network.
 E410414 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: Rudow | Statement: [Berlin U-Bahn line U7, terminus, Rudow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Rudow
Context triple: [Berlin U-Bahn line U7, terminus, Rudow]
  • A. Ruda
    Ruda is the former name of the global sportswear and athletic brand now known as Puma.
  • B. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • C. Rood
    Rood is a surname most notably associated with Ogden Rood, an American physicist and color theorist known for his influential work on color science.
  • D. Rùm
    Rùm is a small, rugged island in Scotland’s Inner Hebrides, known for its dramatic mountainous landscape, wildlife, and status as a National Nature Reserve.
  • E. Ruodhaid
    Ruodhaid was one of Charlemagne’s daughters, a Carolingian princess known primarily through her familial connection to the Frankish emperor.
  • 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: Rudow
Triple: [Berlin U-Bahn line U7, terminus, Rudow]
Generated description
Rudow is a district in the southeastern part of Berlin, Germany, known for its residential character and connection to the city's U-Bahn network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Rudow
Target entity description: Rudow is a district in the southeastern part of Berlin, Germany, known for its residential character and connection to the city's U-Bahn network.
  • A. Ruda
    Ruda is the former name of the global sportswear and athletic brand now known as Puma.
  • B. Blau
    The Blau is a small river in the German state of Baden-Württemberg that flows through the city of Blaustein before joining the Danube.
  • C. Rood
    Rood is a surname most notably associated with Ogden Rood, an American physicist and color theorist known for his influential work on color science.
  • D. Rùm
    Rùm is a small, rugged island in Scotland’s Inner Hebrides, known for its dramatic mountainous landscape, wildlife, and status as a National Nature Reserve.
  • E. Ruodhaid
    Ruodhaid was one of Charlemagne’s daughters, a Carolingian princess known primarily through her familial connection to the Frankish emperor.
  • 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_69aed93c69208190a4efac0efe3cd69b completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefbd4acb0819093bcffcd05ed8e6f completed March 9, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69b562a98c488190a7e77cd46ff998bc completed March 14, 2026, 1:29 p.m.
NEDg Description generation batch_69b5637e72948190989169b0a46916a8 completed March 14, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69b563fc4cb081908ba0f1a799338a8c completed March 14, 2026, 1:34 p.m.
Created at: March 9, 2026, 3:38 p.m.