Triple

T14350724
Position Surface form Disambiguated ID Type / Status
Subject MF 67 E355842 entity
Predicate successorRollingStockType P84259 FINISHED
Object MF 19 E754118 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 19 | Statement: [MF 67, successorRollingStockType, MF 19]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MF 19
Context triple: [MF 67, successorRollingStockType, MF 19]
  • A. MF 19 chosen
    MF 19 is a planned new generation of Paris Métro rubber-tyred rolling stock intended to replace older MF-series trains on several lines.
  • B. 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.
  • C. MF 01
    MF 01 is a class of modern steel-wheeled electric multiple unit trains used on several lines of the Paris Métro.
  • D. 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.
  • E. 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.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f4e1e588190bdc7aaf7a2819948 completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c4335e481909d4db39b8d25edc9 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:14 a.m.