Triple

T2280434
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Metro E51267 entity
Predicate hasLine P35 FINISHED
Object Line 9
Line 9 is a major Barcelona Metro line designed as a long, partially automated route connecting key suburban and airport areas with the wider metropolitan network.
 E249581 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 9 | Statement: [Barcelona Metro, hasLine, Line 9]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 9
Context triple: [Barcelona Metro, hasLine, Line 9]
  • A. Line 9
    Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
  • B. Line 9
    Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
  • C. Line 9
    Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
  • D. Line 8
    Line 8 is a route of Mexico City’s Metrobús bus rapid transit system, serving key corridors with dedicated lanes and station platforms.
  • E. Line 8
    Line 8 is a line of the Mexico City Metro system that runs in a generally north–south direction, connecting key residential and commercial areas of the city.
  • 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 9
Triple: [Barcelona Metro, hasLine, Line 9]
Generated description
Line 9 is a major Barcelona Metro line designed as a long, partially automated route connecting key suburban and airport areas with the wider metropolitan network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 9
Target entity description: Line 9 is a major Barcelona Metro line designed as a long, partially automated route connecting key suburban and airport areas with the wider metropolitan network.
  • A. Line 9
    Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
  • B. Line 9
    Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
  • C. Line 9
    Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
  • D. Line 8
    Line 8 is a route of Mexico City’s Metrobús bus rapid transit system, serving key corridors with dedicated lanes and station platforms.
  • E. Line 8
    Line 8 is a line of the Mexico City Metro system that runs in a generally north–south direction, connecting key residential and commercial areas of the city.
  • 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_69ae71e48fb081908498f826167020a2 completed March 9, 2026, 7:08 a.m.
NEDg Description generation batch_69ae72bf22088190a2c111a71eb0dda7 completed March 9, 2026, 7:11 a.m.
NED2 Entity disambiguation (via description) batch_69ae731ab8bc819090fac5b311cb5fe0 completed March 9, 2026, 7:13 a.m.
Created at: March 4, 2026, 7:48 p.m.