Triple

T10517796
Position Surface form Disambiguated ID Type / Status
Subject UO E248077 entity
Predicate identifierFor P3732 FINISHED
Object HK Express flights E49553 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: HK Express flights | Statement: [UO, identifierFor, HK Express flights]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HK Express flights
Context triple: [UO, identifierFor, HK Express flights]
  • A. HK Express chosen
    HK Express is a Hong Kong-based low-cost airline operating regional flights across Asia.
  • B. China Express Airlines
    China Express Airlines is a Chinese regional carrier that operates domestic and short-haul international flights, primarily serving smaller cities and regional airports across China.
  • C. Air Hong Kong
    Air Hong Kong is a Hong Kong-based all-cargo airline that primarily operates regional freight services across Asia.
  • D. Airphil Express
    Airphil Express was a Philippine low-cost airline that operated domestic and regional flights before being rebranded as PAL Express, a subsidiary of Philippine Airlines.
  • E. Sky Express
    Sky Express is a Greek regional airline that operates domestic flights connecting numerous islands and mainland cities within Greece.
  • 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_69d381c4aa948190942e1d803143fb0e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d509cd0fb8819087de2f9a93bad6e6 completed April 7, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69d94b13f4fc8190863d6e1aa7da5733 completed April 10, 2026, 7:10 p.m.
Created at: April 6, 2026, 12:28 p.m.