Triple

T1946909
Position Surface form Disambiguated ID Type / Status
Subject Sheremetyevo International Airport E42073 entity
Predicate hasTerminal P182 FINISHED
Object Terminal B E42076 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: Terminal B | Statement: [Sheremetyevo International Airport, hasTerminal, Terminal B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal B
Context triple: [Sheremetyevo International Airport, hasTerminal, Terminal B]
  • A. Terminal B
    Terminal B is one of the passenger terminals at Vnukovo International Airport in Moscow, serving as a key facility for handling flights and travelers.
  • B. Terminal B chosen
    Terminal B is one of the passenger terminals at Sheremetyevo International Airport in Moscow, serving as a hub for domestic and selected international flights.
  • C. Terminal B
    Terminal B is a passenger terminal at San Jose International Airport serving commercial airline flights and travelers in San Jose, California.
  • D. Terminal B
    Terminal B is one of the main passenger terminals at Boston Logan International Airport, serving numerous domestic and some international flights with multiple airlines.
  • E. Terminal B
    Terminal B is one of the main passenger terminals at Newark Liberty International Airport, serving a mix of domestic and international flights with multiple concourses and airline operators.
  • 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_69a8870e08fc8190a319cbf2600db15f completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb32ebae881908f7541301f0198ae completed March 7, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae03180a248190a0df96066923728a completed March 8, 2026, 11:15 p.m.
Created at: March 4, 2026, 7:36 p.m.