Triple

T1825007
Position Surface form Disambiguated ID Type / Status
Subject Aeroexpress train E40632 entity
Predicate operator P179 FINISHED
Object Aeroexpress E40632 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: Aeroexpress | Statement: [Aeroexpress train, operator, Aeroexpress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aeroexpress
Context triple: [Aeroexpress train, operator, Aeroexpress]
  • A. Aeroexpress train chosen
    The Aeroexpress train is a dedicated high-speed rail service that connects central Moscow with major airports, including Domodedovo International Airport.
  • B. Capital Airport Express
    Capital Airport Express is a dedicated rapid transit line in the Beijing Subway system that connects central Beijing with Beijing Capital International Airport.
  • C. Leonardo Express train
    The Leonardo Express train is a dedicated non-stop rail service linking central Rome’s Termini station with Fiumicino Airport, providing a fast and frequent airport transfer for travelers.
  • D. Heathrow Express
    Heathrow Express is a non-stop high-speed train service linking London Paddington station with Heathrow Airport, providing one of the fastest rail connections between central London and the airport.
  • E. AeroTrain
    AeroTrain is an automated underground people mover system that transports passengers between terminals at Washington Dulles International Airport.
  • 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_69a8864644bc8190b2358ab897194ac1 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb0003d308190a024f8c03c5f5dad completed March 7, 2026, 4:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69adbf6927fc8190ad9ce95c92153c64 completed March 8, 2026, 6:26 p.m.
Created at: March 4, 2026, 7:32 p.m.