Triple

T15788850
Position Surface form Disambiguated ID Type / Status
Subject San Blas-Canillejas E382808 entity
Predicate hasMetroLine P17559 FINISHED
Object Line 5
Line 5 is a major line of the Madrid Metro system known for connecting central Madrid with several eastern and western districts.
E1177253 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 5 | Statement: [San Blas-Canillejas, hasMetroLine, Line 5]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Line 5
Context triple: [San Blas-Canillejas, hasMetroLine, Line 5]
  • A. Line 5
    Line 5 is a rapid transit line of the Shanghai Metro system serving the southern suburbs of the city.
  • B. Line 5
    Line 5 is one of the main lines of the Paris Métro, running in a generally north–south direction and serving several key stations and neighborhoods across the city.
  • C. Line 5
    Line 5 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
  • D. Line 5
    Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • E. Line 5
    Line 5 is one of the routes of the Tunis Metro light rail network, serving passengers across part of the Tunis metropolitan area.
  • 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 5
Triple: [San Blas-Canillejas, hasMetroLine, Line 5]
Generated description
Line 5 is a major line of the Madrid Metro system known for connecting central Madrid with several eastern and western districts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Line 5
Target entity description: Line 5 is a major line of the Madrid Metro system known for connecting central Madrid with several eastern and western districts.
  • A. Line 5
    Line 5 is a major line of the Barcelona Metro rapid transit system, serving numerous key neighborhoods and transport hubs across the city.
  • B. Line 5
    Line 5 is one of the main lines of the Saint Petersburg Metro system, forming part of the city’s rapid transit network.
  • C. Line 5
    Line 5 is one of the lines of the Mexico City Metro system, serving multiple stations across the city as part of its rapid transit network.
  • D. Line 5
    Line 5 is one of the main lines of the Santiago Metro in Chile, running across several key districts and serving as a major east–west transit corridor in the city.
  • E. Line 5
    Line 5 is a major east–west route of the Brussels Metro system, connecting key districts across the Belgian capital.
  • 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_69d86da16e188190b89af699f1ed0bfe completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e054048ff48190ad107c890ef73166 completed April 16, 2026, 3:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff90a87e3c8190a1c5b13cbfdff54a completed May 9, 2026, 7:53 p.m.
NEDg Description generation batch_69ff949339b88190bd105ffa0c169b54 completed May 9, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_69ff950e053881908d207f4c172e2ea4 completed May 9, 2026, 8:11 p.m.
Created at: April 10, 2026, 4:48 a.m.