Triple

T2280437
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Metro E51267 entity
Predicate hasLine P35 FINISHED
Object Line 12
Line 12 is a planned or lesser-known route within the Barcelona Metro network intended to expand urban rail connectivity in the metropolitan area.
 E254934 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 12 | Statement: [Barcelona Metro, hasLine, Line 12]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 12
Context triple: [Barcelona Metro, hasLine, Line 12]
  • A. Line 12
    Line 12 is a major Mexico City Metro route known for being one of the system’s newest and most modern lines, connecting southeastern districts across a long east–west corridor.
  • B. Line 12
    Line 12 is a rapid transit line of the Shanghai Metro system that runs east–west across the city, connecting several key commercial and residential districts.
  • C. Line 13
    Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
  • D. Line 13
    Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
  • E. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • 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 12
Triple: [Barcelona Metro, hasLine, Line 12]
Generated description
Line 12 is a planned or lesser-known route within the Barcelona Metro network intended to expand urban rail connectivity in the metropolitan area.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 12
Target entity description: Line 12 is a planned or lesser-known route within the Barcelona Metro network intended to expand urban rail connectivity in the metropolitan area.
  • A. Line 12
    Line 12 is a major Mexico City Metro route known for being one of the system’s newest and most modern lines, connecting southeastern districts across a long east–west corridor.
  • B. Line 12
    Line 12 is a rapid transit line of the Shanghai Metro system that runs east–west across the city, connecting several key commercial and residential districts.
  • C. Line 13
    Line 13 is a suburban loop line of the Beijing Subway that serves the northern part of the city and connects several major transfer stations.
  • D. Line 13
    Line 13 is a major rapid transit route in the Shanghai Metro system that serves key urban districts and supports heavy commuter traffic across the city.
  • E. Line 13
    Line 13 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China.
  • 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_69a88b08e4308190bdac9aebcca1c91a completed March 4, 2026, 7:42 p.m.
NER Named-entity recognition batch_69abc21ac3d48190abef254e1c3f45e8 completed March 7, 2026, 6:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae894cbb788190826b27cefb856651 completed March 9, 2026, 8:48 a.m.
NEDg Description generation batch_69ae8a98a4108190995ef759d2c4de85 completed March 9, 2026, 8:53 a.m.
NED2 Entity disambiguation (via description) batch_69ae8af889b48190b39ae193869a3aad completed March 9, 2026, 8:55 a.m.
Created at: March 4, 2026, 7:48 p.m.