Triple

T2069946
Position Surface form Disambiguated ID Type / Status
Subject Copa Airlines E45992 entity
Predicate hasCodeShareAgreementWith P10967 FINISHED
Object KLM E31984 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: KLM | Statement: [Copa Airlines, hasCodeShareAgreementWith, KLM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KLM
Context triple: [Copa Airlines, hasCodeShareAgreementWith, KLM]
  • A. KLM chosen
    KLM is the flag carrier airline of the Netherlands and one of the world's oldest airlines still operating under its original name.
  • B. KLM Cityhopper
    KLM Cityhopper is a Dutch regional airline and subsidiary of KLM that operates short-haul flights across Europe, primarily feeding traffic into KLM’s main network.
  • C. Transavia
    Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
  • D. Brussels Airlines
    Brussels Airlines is the flag carrier airline of Belgium, operating flights across Europe, Africa, and other regions as part of the Lufthansa Group.
  • E. Martinair
    Martinair is a Dutch airline based in the Netherlands that operates both cargo and charter passenger services, historically linked to KLM.
  • 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_69a8891b38288190abd572ccad9b6928 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abb9f677108190aea3c8db7850c892 completed March 7, 2026, 5:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae30547b288190ab9466686f749768 completed March 9, 2026, 2:28 a.m.
Created at: March 4, 2026, 7:41 p.m.