Triple

T12500863
Position Surface form Disambiguated ID Type / Status
Subject Moscow–Paris E298815 entity
Predicate servedByTransportInfrastructure P51097 FINISHED
Object airports 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: airports | Statement: [Moscow–Paris, servedByTransportInfrastructure, airports]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: servedByTransportInfrastructure
Context triple: [Moscow–Paris, servedByTransportInfrastructure, airports]
  • A. usedTransportationInfrastructure
    Indicates that an entity made use of some form of transportation infrastructure (such as roads, railways, or ports) to enable movement or transit.
  • B. typeOfTransportInfrastructure
    Indicates the specific category or kind of transport infrastructure associated with or used in a given context.
  • C. operatorOfTransportInfrastructure
    Indicates that an entity operates, manages, or runs a specific piece of transport infrastructure.
  • D. shareTransportInfrastructure
    Indicates that multiple entities make joint use of the same transport infrastructure facilities or systems.
  • E. hasMajorTransportInfrastructure chosen
    Indicates that a location possesses significant transportation facilities or networks, such as major roads, railways, ports, or airports, that support substantial movement of people or goods.
  • F. None of above.

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_69d6ada4cd388190ae3bbf83ff87057a completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94e8a706c8190873623eab7db607d completed April 10, 2026, 7:24 p.m.
PD Predicate disambiguation batch_69d94d41f3cc8190a3331fb9a895306f completed April 10, 2026, 7:19 p.m.
Created at: April 8, 2026, 9:57 p.m.