Triple

T107672
Position Surface form Disambiguated ID Type / Status
Subject Orly Airport E2174 entity
Predicate wasMainParisAirportBefore P7894 FINISHED
Object Charles de Gaulle Airport opening 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: Charles de Gaulle Airport opening | Statement: [Orly Airport, wasMainParisAirportBefore, Charles de Gaulle Airport opening]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: wasMainParisAirportBefore
Context triple: [Orly Airport, wasMainParisAirportBefore, Charles de Gaulle Airport opening]
  • A. hasMajorAirport
    Indicates that a location possesses at least one significant airport that serves as a primary hub for air travel in that area.
  • B. capitalOfProvincePreviouslyLocatedOn
    Indicates that an entity serves or served as the capital city of a province that was formerly situated in a specified location.
  • C. hasInternationalAirport
    Indicates that a place possesses an airport that handles international flights and services cross-border air traffic.
  • D. wasFirstCapitalOf
    Indicates that one place previously served as the earliest or original capital city of another political or administrative entity.
  • E. largestAirport
    Indicates that one airport is the largest (typically by area, traffic, or capacity) among a specified set or within a given region.
  • 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_69a24fcdaeb48190a2d796677e4b3281 completed Feb. 28, 2026, 2:15 a.m.
NER Named-entity recognition batch_69a25a1199ac8190ac65ffaaf45b4f5b completed Feb. 28, 2026, 2:59 a.m.
PD Predicate disambiguation batch_69a2563e7188819091e9a94e071991d7 completed Feb. 28, 2026, 2:43 a.m.
PDg Predicate description generation batch_69a25a10d6448190bee47847d5c13b84 completed Feb. 28, 2026, 2:59 a.m.
Created at: Feb. 28, 2026, 2:20 a.m.