Triple

T13856200
Position Surface form Disambiguated ID Type / Status
Subject Bel-Air (Paris Métro) E333069 entity
Predicate hasRollingStockType P1305 FINISHED
Object MF 01 E199145 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: MF 01 | Statement: [Bel-Air (Paris Métro), hasRollingStockType, MF 01]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MF 01
Context triple: [Bel-Air (Paris Métro), hasRollingStockType, MF 01]
  • A. MF 01 chosen
    MF 01 is a class of modern steel-wheeled electric multiple unit trains used on several lines of the Paris Métro.
  • B. MF 19
    MF 19 is a planned new generation of Paris Métro rubber-tyred rolling stock intended to replace older MF-series trains on several lines.
  • C. MF 77
    MF 77 is a steel-wheeled electric multiple unit train used on several lines of the Paris Métro, introduced in the late 1970s to modernize the network’s rolling stock.
  • D. MF 67
    MF 67 is a class of steel-wheeled electric multiple unit trains that have long served as a primary rolling stock type on the Paris Métro.
  • E. MF 88
    MF 88 is a type of rubber-tyred electric multiple unit train used on the Paris Métro, notable for its experimental design and limited deployment.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02dc9f488190b7181dcb7e304632 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0fb7c3c819081fc6f89aa17d6af completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.