Triple

T2337194
Position Surface form Disambiguated ID Type / Status
Subject KSJC E44337 entity
Predicate hasTerminal P182 FINISHED
Object Terminal B E49040 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: [KSJC, hasTerminal, Terminal B]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal B
Context triple: [KSJC, 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
    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.
  • C. Terminal B
    Terminal B is one of the passenger terminals at Sheremetyevo International Airport in Moscow, serving as a hub for domestic and selected international flights.
  • D. Terminal B chosen
    Terminal B is a passenger terminal at San Jose International Airport serving commercial airline flights and travelers in San Jose, California.
  • E. Terminal B
    Terminal B is one of the passenger terminals at Dallas/Fort Worth International Airport, serving various domestic and regional flights with gates, check-in, and passenger amenities.
  • 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_69a889132b488190bbb43ad4780ddd92 completed March 4, 2026, 7:33 p.m.
NER Named-entity recognition batch_69abc68ac4348190ab6ec46ec7879643 completed March 7, 2026, 6:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae961adfdc8190bf79d479d8207599 completed March 9, 2026, 9:42 a.m.
Created at: March 4, 2026, 7:51 p.m.