Triple

T6041890
Position Surface form Disambiguated ID Type / Status
Subject CP E134564 entity
Predicate assignedTo P3151 FINISHED
Object Canadian Airlines E25115 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: Canadian Airlines | Statement: [CP, assignedTo, Canadian Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Canadian Airlines
Context triple: [CP, assignedTo, Canadian Airlines]
  • A. Canadian Airlines chosen
    Canadian Airlines was a former major Canadian carrier that operated extensive domestic and international routes before being acquired by Air Canada in 2000.
  • B. Air Canada
    Air Canada is the flag carrier and largest airline of Canada, operating extensive domestic and international passenger and cargo services.
  • C. Canadian Pacific Air Lines
    Canadian Pacific Air Lines was a major Canadian airline that operated extensive domestic and international routes before becoming a key component of the later Canadian Airlines through merger.
  • D. WestJet
    WestJet is a major Canadian low-cost airline known for its extensive domestic and international route network and customer-friendly service.
  • E. Nordair
    Nordair was a former Canadian regional airline that operated passenger and cargo services, particularly in northern and remote areas, before being absorbed into larger national carriers.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056d11370819096ac35349bd91f4e completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1139793708190b14c83d4197a33a0 completed March 23, 2026, 10:19 a.m.
Created at: March 22, 2026, 4:08 p.m.