Triple

T2142530
Position Surface form Disambiguated ID Type / Status
Subject Paris Orly Airport E46790 entity
Predicate servesAsHubFor P423 FINISHED
Object French Bee E10909 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: French Bee | Statement: [Paris Orly Airport, servesAsHubFor, French Bee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: French Bee
Context triple: [Paris Orly Airport, servesAsHubFor, French Bee]
  • A. French Bee chosen
    French Bee is a French low-cost, long-haul airline specializing in transatlantic and Indian Ocean routes.
  • B. Barberini bees
    The Barberini bees are a heraldic emblem of the powerful Italian Barberini family, prominently associated with Pope Urban VIII and widely used in Baroque art and architecture in Rome.
  • C. The Bee
    The Bee is the 16th chapter of the Qur'an, known for its emphasis on God's blessings, signs in nature, and guidance for righteous living.
  • D. Angoumois
    Angoumois is a historic province in western France centered around the town of Angoulême, known for its role in the old French provincial system.
  • E. Sauvy
    Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe206db0819095772af5358dca55 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae51b63e4081908a5d87af5d17d3c4 completed March 9, 2026, 4:51 a.m.
Created at: March 4, 2026, 7:44 p.m.