Triple

T11040402
Position Surface form Disambiguated ID Type / Status
Subject TMB 6000 series E260997 entity
Predicate hasOperator P179 FINISHED
Object TMB E878171 NE FINISHED

How this triple was built (2 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 | Statement: [TMB 6000 series, hasOperator, TMB]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TMB
Context triple: [TMB 6000 series, hasOperator, TMB]
  • A. 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.
  • B. TMB chosen
    TMB is the main public transportation operator in the Barcelona metropolitan area, managing the city’s metro and bus networks.
  • C. TMB App
    TMB App is the official mobile application for Barcelona’s public transport network, providing route planning, real-time information, and ticketing services for metro, bus, and other transit options.
  • 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 7000 series
    The TMB 7000 series is a class of modern electric multiple unit trains used on the Barcelona Metro network.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa979bdc8190bf0e79104cc098c1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797ff519481909ebc2515b3d241de completed April 9, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a9d61b548190949f0dfbcb782064 completed April 18, 2026, 3:57 p.m.
Created at: April 8, 2026, 9:26 p.m.