Triple

T2843173
Position Surface form Disambiguated ID Type / Status
Subject Boston Logan International Airport E62516 entity
Predicate hasTerminal P182 FINISHED
Object Terminal E E50180 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 E | Statement: [Boston Logan International Airport, hasTerminal, Terminal E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal E
Context triple: [Boston Logan International Airport, hasTerminal, Terminal E]
  • A. Terminal E chosen
    Terminal E is the international terminal at Boston Logan International Airport, serving most of the airport’s overseas flights and customs operations.
  • B. Terminal E
    Terminal E is one of the passenger terminals at Sheremetyevo International Airport in Moscow, serving international flights with modern facilities and connections to adjacent terminals.
  • C. Terminal E
    Terminal E is one of the passenger terminals at Dallas/Fort Worth International Airport, serving various domestic and some international flights with multiple gates and amenities.
  • D. Terminal E
    Terminal E is one of the passenger terminals at Philadelphia International Airport, primarily serving domestic airline operations and regional flights.
  • E. Terminal D
    Terminal D is one of the main passenger terminals at Sheremetyevo International Airport in Moscow, serving numerous international and domestic flights.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf1898748190b031a2bd2091c0c0 completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8d570388190b4ed81ace605c6c3 completed March 10, 2026, 9:48 a.m.
Created at: March 6, 2026, 10:01 p.m.