Triple

T22887761
Position Surface form Disambiguated ID Type / Status
Subject Bonn public transport network E567650 entity
Predicate hasLightRailLine P473 FINISHED
Object Line 68
Line 68 is a light rail route within Bonn’s public transport system that connects key districts and suburbs in the city and surrounding region.
 E1562924 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: Line 68 | Statement: [Bonn public transport network, hasLightRailLine, Line 68]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 68
Context triple: [Bonn public transport network, hasLightRailLine, Line 68]
  • A. Line 67
    Line 67 is a light rail route within Bonn’s public transport system, providing urban and suburban passenger service as part of the city’s Stadtbahn network.
  • B. Line 66
    Line 66 is a major light rail route in Bonn’s public transport system, connecting key districts and serving as an important commuter corridor in the region.
  • C. Line 62
    Line 62 is a tram route within Bonn’s public transport system that serves local passengers along its designated corridor in the city.
  • D. Line 63
    Line 63 is a light rail route within Bonn’s Stadtbahn network that connects key districts of the city and surrounding areas.
  • E. Line 59
    Line 59 is a Belgian railway line that connects the cities of Ghent and Antwerp.
  • 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: Line 68
Triple: [Bonn public transport network, hasLightRailLine, Line 68]
Generated description
Line 68 is a light rail route within Bonn’s public transport system that connects key districts and suburbs in the city and surrounding region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 68
Target entity description: Line 68 is a light rail route within Bonn’s public transport system that connects key districts and suburbs in the city and surrounding region.
  • A. Line 67
    Line 67 is a light rail route within Bonn’s public transport system, providing urban and suburban passenger service as part of the city’s Stadtbahn network.
  • B. Line 66
    Line 66 is a major light rail route in Bonn’s public transport system, connecting key districts and serving as an important commuter corridor in the region.
  • C. Line 62
    Line 62 is a tram route within Bonn’s public transport system that serves local passengers along its designated corridor in the city.
  • D. Line 63
    Line 63 is a light rail route within Bonn’s Stadtbahn network that connects key districts of the city and surrounding areas.
  • E. Line 59
    Line 59 is a Belgian railway line that connects the cities of Ghent and Antwerp.
  • 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_69e2458a92ec81908fc1cd5f6407d2ab completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17fc2adb4819081bce7e6849ba31a completed April 29, 2026, 3:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bca08d3348190b84e7d7d9b1e17fe completed May 19, 2026, 2:25 a.m.
NEDg Description generation batch_6a0bcabd0cbc81909fc773fe62a3efbf completed May 19, 2026, 2:28 a.m.
NED2 Entity disambiguation (via description) batch_6a0bcb7ccc4881909fe70749449c0e6c completed May 19, 2026, 2:31 a.m.
Created at: April 17, 2026, 3:40 p.m.