Triple

T2218865
Position Surface form Disambiguated ID Type / Status
Subject Paris–Le Bourget Airport E48093 entity
Predicate operator P179 FINISHED
Object Groupe ADP E11760 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: Groupe ADP | Statement: [Paris–Le Bourget Airport, operator, Groupe ADP]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Groupe ADP
Context triple: [Paris–Le Bourget Airport, operator, Groupe ADP]
  • A. Groupe ADP chosen
    Groupe ADP is a major French airport management company that owns and operates the Paris-area airports and provides aviation and related services worldwide.
  • B. Omnicom Group
    Omnicom Group is a global marketing and communications holding company that owns numerous leading advertising, media, and public relations agencies worldwide.
  • C. SAS Group
    SAS Group is a Scandinavian airline holding company that operates Scandinavian Airlines and related aviation businesses across Northern Europe.
  • D. Publicis Groupe
    Publicis Groupe is a major French multinational advertising and communications company and one of the world’s largest marketing services groups.
  • E. The Advisory Board Company
    The Advisory Board Company is a research, consulting, and technology firm that provides strategic insights and performance-improvement services primarily to healthcare and higher education organizations.
  • 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_69a88aa1ee708190862c8c378c41e9eb completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc011d50c8190b1c375cc633f8189 completed March 7, 2026, 6:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6afc6dd881909dd51d8a18ab4c74 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:46 p.m.