Triple

T10047110
Position Surface form Disambiguated ID Type / Status
Subject Cité E207642 entity
Predicate network P2637 FINISHED
Object Paris Métro network E41186 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: Paris Métro network | Statement: [Cité, network, Paris Métro network]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris Métro network
Context triple: [Cité, network, Paris Métro network]
  • A. Paris Metro chosen
    The Paris Metro is the extensive rapid transit system serving Paris and its suburbs, known for its dense network, Art Nouveau station entrances, and central role in the city’s public transportation.
  • B. Paris Métro Gare du Nord
    Paris Métro Gare du Nord is a major Parisian underground station and interchange hub serving multiple metro and RER lines beneath the Gare du Nord railway terminus.
  • C. Paris Métro Gare de Lyon
    Paris Métro Gare de Lyon is a major Parisian underground station and transport hub serving multiple metro and RER lines beneath the Gare de Lyon mainline railway terminal.
  • D. Paris Métro Poissonnière
    Paris Métro Poissonnière is a station on the Paris Métro network located in the 10th arrondissement, serving Line 7 near the Gare du Nord area.
  • E. Lyon Metro
    Lyon Metro is the rapid transit system serving the French city of Lyon and its suburbs, known for its rubber-tyred lines and integration with the city’s broader public transport 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_69ca835ad0608190b7c80b292da004f5 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cdcf664dd881908786fcd802bf10da completed April 2, 2026, 2:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a4064a48190b4fdb6bf3ea5af05 completed April 5, 2026, 5:22 p.m.
Created at: March 30, 2026, 8:56 p.m.