Triple

T16061575
Position Surface form Disambiguated ID Type / Status
Subject SkyTeam E389626 entity
Predicate hasMember P10 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: [SkyTeam, hasMember, KLM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KLM
Context triple: [SkyTeam, hasMember, 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 line
    The KLM line was a legendary Soviet ice hockey forward trio featuring Vladimir Krutov, Igor Larionov, and Sergei Makarov, renowned for their skill, chemistry, and dominance in international play.
  • C. 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.
  • D. Transavia
    Transavia is a Dutch low-cost airline operating scheduled and charter flights across Europe and North Africa.
  • E. 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.
  • 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_69d86dae698881908327ef2d67706cb9 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e183795100819097be92e6d07dc5b1 completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffdbe88a608190bc0a0cbfdb71e81d completed May 10, 2026, 1:14 a.m.
Created at: April 10, 2026, 4:57 a.m.