Triple

T4421657
Position Surface form Disambiguated ID Type / Status
Subject TO E95110 entity
Predicate airlineMarketSegment P55881 FINISHED
Object leisure travel LITERAL 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: leisure travel | Statement: [TO, airlineMarketSegment, leisure travel]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: airlineMarketSegment
Context triple: [TO, airlineMarketSegment, leisure travel]
  • A. airlineMarket
    Indicates a commercial air transport relationship where an airline provides or operates flight services within a specific origin–destination market or route.
  • B. airlineCategory
    Indicates the classification or type of an airline within a defined categorization system (e.g., full-service, low-cost, regional).
  • C. servesAirline
    Indicates that a transportation facility or location provides service for, or is regularly used by, a specified airline.
  • D. airlineHub
    Indicates that a particular location (typically an airport or city) serves as a central hub or primary operational base for an airline.
  • E. servesAirlineType
    Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
  • F. None of above. chosen

Provenance (4 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3554a0e7c8190b704d00d07b1857d completed March 13, 2026, 12:07 a.m.
PD Predicate disambiguation batch_69b34f5eabe88190a12b244ea71e46d6 completed March 12, 2026, 11:42 p.m.
PDg Predicate description generation batch_69b3505a87b4819083fbbd58870e520b completed March 12, 2026, 11:46 p.m.
Created at: March 12, 2026, 11:30 p.m.