Triple

T10173386
Position Surface form Disambiguated ID Type / Status
Subject McDonnell Douglas MD-11 E235787 entity
Predicate primaryUsers P98 FINISHED
Object UPS Airlines E87866 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: UPS Airlines | Statement: [McDonnell Douglas MD-11, primaryUsers, UPS Airlines]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UPS Airlines
Context triple: [McDonnell Douglas MD-11, primaryUsers, UPS Airlines]
  • A. UPS Airlines chosen
    UPS Airlines is a major American cargo airline and the air freight division of United Parcel Service, operating a global network of package and logistics flights.
  • B. United Express
    United Express is the regional brand for United Airlines, operating shorter-haul feeder flights to connect passengers to United’s mainline network.
  • C. United Airlines
    United Airlines is a major American airline and Star Alliance member known for its extensive domestic and international route network operated from multiple hubs across the United States.
  • D. Ultra Worldwide
    Ultra Worldwide is the global brand and network of international electronic music festivals and events associated with the Ultra Music Festival.
  • E. UTAIR
    UTAIR is a Russian airline that operates domestic and international passenger and cargo flights, with a significant presence in regional and helicopter services.
  • 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_69ca84d1d5f88190ab878a1021ecff68 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec9f6dd8819081588600499165ee completed April 2, 2026, 4:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d3010c386481908bc0c985c0b5ff93 completed April 6, 2026, 12:40 a.m.
Created at: March 30, 2026, 9:10 p.m.