Triple

T9732228
Position Surface form Disambiguated ID Type / Status
Subject Paris Métro Line 3 E235772 entity
Predicate rollingStock P1305 FINISHED
Object MF 67 E206990 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 67 | Statement: [Paris Métro Line 3, rollingStock, MF 67]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: MF 67
Context triple: [Paris Métro Line 3, rollingStock, MF 67]
  • A. MF 67 chosen
    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.
  • 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 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.
  • D. 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.
  • E. MfS
    MfS was the official state security and intelligence service of the former East Germany, widely known for its extensive surveillance and repression of the population.
  • 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_69ca84d0fad481909cdd45aa77416c48 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9eb3d6e4819090b3c7fb92550c57 completed April 1, 2026, 10:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69d19fbbba2081909a15725a68423162 completed April 4, 2026, 11:33 p.m.
Created at: March 30, 2026, 8:22 p.m.