Triple

T13843107
Position Surface form Disambiguated ID Type / Status
Subject French Bee E332715 entity
Predicate mainFrenchAirport P8171 FINISHED
Object Paris Orly Airport E46790 NE FINISHED

How this triple was built (3 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: Paris Orly Airport | Statement: [French Bee, mainFrenchAirport, Paris Orly Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paris Orly Airport
Context triple: [French Bee, mainFrenchAirport, Paris Orly Airport]
  • A. Paris Orly Airport chosen
    Paris Orly Airport is a major international airport serving the Paris metropolitan area, located south of the city and handling a large share of its domestic and European flights.
  • B. Paris–Le Bourget Airport
    Paris–Le Bourget Airport is a historic airport near Paris that now primarily serves business aviation and hosts the biennial Paris Air Show.
  • C. Charles de Gaulle Airport
    Charles de Gaulle Airport is the largest international airport in France and a major European aviation hub serving the Paris metropolitan area.
  • D. Strasbourg Airport
    Strasbourg Airport is an international airport serving the city of Strasbourg and the surrounding Alsace region in northeastern France.
  • E. Lyon–Saint-Exupéry Airport
    Lyon–Saint-Exupéry Airport is a major international airport in eastern France serving the city of Lyon and the surrounding Auvergne-Rhône-Alpes region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mainFrenchAirport
Context triple: [French Bee, mainFrenchAirport, Paris Orly Airport]
  • A. otherMainParisAirport
    Indicates that one airport serves as an alternative primary airport to another in the Paris area.
  • B. airportRankInFranceByTraffic
    Indicates the relative position of an airport in France when airports are ordered by the volume of passenger or cargo traffic they handle.
  • C. primaryFrenchDestination
    Indicates that one entity is the main or most significant travel destination in France for another entity.
  • D. wasMainParisAirportBefore
    Indicates that an airport served as the primary or principal airport for Paris during a specified earlier time period.
  • E. hubAirport chosen
    Indicates that an airport serves as a primary hub or central operating base for a particular airline or carrier.
  • F. None of above.

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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02afce788190a74dce4e6a3569fa completed April 14, 2026, 9:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69fcdeefd61c81908d189237af45467a completed May 7, 2026, 6:50 p.m.
PD Predicate disambiguation batch_69dbc86668e08190ba9135d1c3f38d35 completed April 12, 2026, 4:29 p.m.
Created at: April 9, 2026, 10:13 p.m.