Triple

T2280464
Position Surface form Disambiguated ID Type / Status
Subject Barcelona Metro E51267 entity
Predicate hasRollingStockType P1305 FINISHED
Object TMB 6000 series
The TMB 6000 series is a class of modern electric multiple-unit trains used on the Barcelona Metro system.
 E260997 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: TMB 6000 series | Statement: [Barcelona Metro, hasRollingStockType, TMB 6000 series]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: TMB 6000 series
Context triple: [Barcelona Metro, hasRollingStockType, TMB 6000 series]
  • A. TMB 5000 series
    The TMB 5000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
  • B. TMB 3000 series
    The TMB 3000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • C. TMB 4000 series
    The TMB 4000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • D. TMB 2000 series
    The TMB 2000 series is a class of electric multiple unit trains used on the Barcelona Metro, designed for high-capacity urban rapid transit service.
  • E. TMB
    TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
  • 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: TMB 6000 series
Triple: [Barcelona Metro, hasRollingStockType, TMB 6000 series]
Generated description
The TMB 6000 series is a class of modern electric multiple-unit trains used on the Barcelona Metro system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: TMB 6000 series
Target entity description: The TMB 6000 series is a class of modern electric multiple-unit trains used on the Barcelona Metro system.
  • A. TMB 5000 series
    The TMB 5000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
  • B. TMB 3000 series
    The TMB 3000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • C. TMB 4000 series
    The TMB 4000 series is a class of electric multiple unit trains used on the Barcelona Metro system for passenger service.
  • D. TMB 2000 series
    The TMB 2000 series is a class of electric multiple unit trains used on the Barcelona Metro, designed for high-capacity urban rapid transit service.
  • E. TMB
    TMB is the commonly used abbreviation for the Technical Management Board, a governing body that oversees and coordinates technical and standardization activities within its organization.
  • 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_69aea86ab4cc8190ba2203c09f72aaa6 completed March 9, 2026, 11 a.m.
NEDg Description generation batch_69aeaa6cb58081909a0897d4cb328063 completed March 9, 2026, 11:09 a.m.
NED2 Entity disambiguation (via description) batch_69aeabb6d43481908899080f6ca58101 completed March 9, 2026, 11:15 a.m.
Created at: March 4, 2026, 7:48 p.m.