Triple

T17427373
Position Surface form Disambiguated ID Type / Status
Subject Charleroi Metro E423773 entity
Predicate hasLine P35 FINISHED
Object Line M4
Line M4 is a light metro route within the Charleroi Metro network in Belgium, serving as one of its urban rapid transit lines.
 E1271667 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 M4 | Statement: [Charleroi Metro, hasLine, Line M4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line M4
Context triple: [Charleroi Metro, hasLine, Line M4]
  • A. Line M3
    Line M3 is a light metro route within the Charleroi Metro network in Belgium, serving suburban areas around the city.
  • B. Line M
    Line M is a cable car line within the Medellín Metro system that serves hillside neighborhoods by connecting them to the city’s main mass transit network.
  • C. Line M1
    Line M1 is a primary metro line of the Warsaw Metro system, running north–south through the city and serving key residential and commercial districts.
  • D. Line M1
    Line M1 is a light metro route within the Charleroi Metro system in Belgium, serving as one of its primary urban transit lines.
  • E. Line M2
    Line M2 is a route of the Charleroi Metro system in Belgium, serving as part of the city's light rail rapid transit 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: Line M4
Triple: [Charleroi Metro, hasLine, Line M4]
Generated description
Line M4 is a light metro route within the Charleroi Metro network in Belgium, serving as one of its urban rapid transit lines.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line M4
Target entity description: Line M4 is a light metro route within the Charleroi Metro network in Belgium, serving as one of its urban rapid transit lines.
  • A. Line M3
    Line M3 is a light metro route within the Charleroi Metro network in Belgium, serving suburban areas around the city.
  • B. Line M
    Line M is a cable car line within the Medellín Metro system that serves hillside neighborhoods by connecting them to the city’s main mass transit network.
  • C. Line M1
    Line M1 is a primary metro line of the Warsaw Metro system, running north–south through the city and serving key residential and commercial districts.
  • D. Line M1
    Line M1 is a light metro route within the Charleroi Metro system in Belgium, serving as one of its primary urban transit lines.
  • E. Line M2
    Line M2 is a route of the Charleroi Metro system in Belgium, serving as part of the city's light rail rapid transit 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_69d889d88b6081908bada047f5b3ba51 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e448fdc1348190985db52c8c74c394 completed April 19, 2026, 3:16 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01c1ef938c8190b7b5deadb1a352bf completed May 11, 2026, 11:47 a.m.
NEDg Description generation batch_6a01c2f2bd0881908b052cb458673259 completed May 11, 2026, 11:52 a.m.
NED2 Entity disambiguation (via description) batch_6a01c3bbaf108190b48d81b2a5ac6fd2 completed May 11, 2026, 11:55 a.m.
Created at: April 10, 2026, 5:46 a.m.