Triple

T13691929
Position Surface form Disambiguated ID Type / Status
Subject Terminal A Station E328286 entity
Predicate serves P98 FINISHED
Object Terminal A unclear NED1 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 A | Statement: [Terminal A Station, serves, Terminal A]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terminal A
Context triple: [Terminal A Station, serves, Terminal A]
  • A. Terminal A
    Terminal A is one of the passenger terminals at Sheremetyevo International Airport in Moscow, serving specific flights and airlines within the airport’s terminal complex.
  • B. Terminal A
    Terminal A is one of the main passenger terminals at San Jose International Airport, serving airline check-in, security, boarding gates, and baggage claim for departing and arriving travelers.
  • C. Terminal A
    Terminal A is one of the passenger terminals at Boston Logan International Airport, serving as a hub for several domestic and international airline operations.
  • D. Terminal A
    Terminal A is one of the main passenger terminals at Trondheim Airport, Værnes in Norway, handling a significant share of the airport’s domestic and/or international air traffic.
  • E. Terminal A
    Terminal A is one of the passenger terminals at Bordeaux–Mérignac Airport, serving as a key facility for handling flights and travelers at the airport.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d8076ff62081908a7bd79889edd7a0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc8746458819095ec1ba3c01ef31b completed April 12, 2026, 4:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7944e7ea0819098a9fbf8842d314b completed May 3, 2026, 6:30 p.m.
Created at: April 9, 2026, 9:53 p.m.