Triple

T15810592
Position Surface form Disambiguated ID Type / Status
Subject George Bush Intercontinental Airport E383338 entity
Predicate hasTerminal P182 FINISHED
Object Terminal E E386305 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: [George Bush Intercontinental Airport, hasTerminal, Terminal E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal E
Context triple: [George Bush Intercontinental Airport, hasTerminal, Terminal E]
  • A. Terminal E
    Terminal E is an international satellite terminal at Zurich Airport primarily serving long-haul and non-Schengen flights.
  • 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 the international terminal at Boston Logan International Airport, serving most of the airport’s overseas flights and customs operations.
  • 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 E chosen
    Terminal E is an international terminal at George Bush Intercontinental Airport in Houston, primarily serving major domestic and long-haul international 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_69d86da2858c819090cc8481e7207b6e completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0b52aae14819091de08630e7e1d1a completed April 16, 2026, 10:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffa131784c8190bd6aba2cca084d20 completed May 9, 2026, 9:03 p.m.
Created at: April 10, 2026, 4:49 a.m.