Triple

T15550463
Position Surface form Disambiguated ID Type / Status
Subject K. I. Sawyer Air Force Base E370728 entity
Predicate hasIATAcode P2569 FINISHED
Object SAW E161448 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: SAW | Statement: [K. I. Sawyer Air Force Base, hasIATAcode, SAW]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SAW
Context triple: [K. I. Sawyer Air Force Base, hasIATAcode, SAW]
  • A. SAW chosen
    SAW is the IATA airport code for Sabiha Gökçen International Airport, a major international airport serving Istanbul, Turkey.
  • B. SAW
    SAW is the abbreviation for the U.S. Marine Corps’ School of Advanced Warfighting, an advanced professional military education institution focused on developing operational-level planners and leaders.
  • C. SA3
    SA3 is the 3GPP security working group responsible for specifying and evolving security architecture and mechanisms across mobile communication standards.
  • D. SAV
    SAV is the National Rail station code for Stratford-upon-Avon railway station in Warwickshire, England.
  • E. SAV
    SAV is the IATA airport code for Savannah/Hilton Head International Airport serving Savannah, Georgia, and the surrounding region.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04a93121881909d88ca55a39252ac completed April 16, 2026, 2:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455dfbcc8190a93e90c59b2d3045 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:08 a.m.