Triple

T9627029
Position Surface form Disambiguated ID Type / Status
Subject SAN VORTAC E232494 entity
Predicate associatedWithAirport P6864 FINISHED
Object KSAN E32610 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: KSAN | Statement: [SAN VORTAC, associatedWithAirport, KSAN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KSAN
Context triple: [SAN VORTAC, associatedWithAirport, KSAN]
  • A. KSAN chosen
    KSAN is the ICAO airport code for San Diego International Airport, a major commercial airport serving the San Diego, California area.
  • B. KSAD
    KSAD is the commonly used abbreviation for the position of Chief of Staff of the Indonesian Army, the highest-ranking officer responsible for leading and managing Indonesia’s land forces.
  • C. KSAT
    KSAT is the ICAO airport code for San Antonio International Airport, a major commercial airport serving the San Antonio, Texas area.
  • D. KSAV
    KSAV is the ICAO airport code for Savannah/Hilton Head International Airport, a commercial and military airfield serving the Savannah, Georgia and Hilton Head Island, South Carolina region.
  • E. KMSKA
    KMSKA is the Royal Museum of Fine Arts in Antwerp, renowned for its extensive collection of Flemish and Belgian art spanning several centuries.
  • 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_69ca848793ec8190a93a12383a754dc0 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9afc9144819084b208c3d04174ba completed April 1, 2026, 10:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1798129dc819090a29efcbcf34b8e completed April 4, 2026, 8:50 p.m.
Created at: March 30, 2026, 8:10 p.m.