Triple

T2280429
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Metro E51267 entity
Predicate hasLine P35 FINISHED
Object Line 1
Line 1 is one of the main lines of the Barcelona Metro rapid transit system, running on a largely east–west axis and serving several key districts of the city.
 E249578 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 1 | Statement: [Barcelona Metro, hasLine, Line 1]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Line 1
Context triple: [Barcelona Metro, hasLine, Line 1]
  • A. Line 1
    Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
  • B. Line 1
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • C. Line 1
    Line 1 is a major rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's primary east–west corridors.
  • D. Line 1
    Line 1 is the main north–south route of the Tehran Metro system, serving as one of its busiest and most important rapid transit lines.
  • E. Line 1
    Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest routes.
  • 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 1
Triple: [Barcelona Metro, hasLine, Line 1]
Generated description
Line 1 is one of the main lines of the Barcelona Metro rapid transit system, running on a largely east–west axis and serving several key districts of the city.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Line 1
Target entity description: Line 1 is one of the main lines of the Barcelona Metro rapid transit system, running on a largely east–west axis and serving several key districts of the city.
  • A. Line 1
    Line 1 is the oldest and one of the busiest lines of the Paris Métro, running primarily east–west through central Paris and serving many major landmarks.
  • B. Line 1
    Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
  • C. Line 1
    Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest routes.
  • D. Line 1
    Line 1 is the main north–south route of the Tehran Metro system, serving as one of its busiest and most important rapid transit lines.
  • E. Line 1
    Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
  • 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.