Triple

T20069789
Position Surface form Disambiguated ID Type / Status
Subject KOFF E499701 entity
Predicate hasRunway P105 FINISHED
Object Runway 12/30
Runway 12/30 is a primary paved runway at KOFF (Offutt Air Force Base) used for military and associated air operations.
 E1422170 NE FINISHED

How this triple was built (4 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: Runway 12/30 | Statement: [KOFF, hasRunway, Runway 12/30]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 12/30
Context triple: [KOFF, hasRunway, Runway 12/30]
  • A. Runway 12/30
    Runway 12/30 is one of the primary paved runways used for aircraft takeoffs and landings at Washington Dulles International Airport in Virginia.
  • B. Runway 12/30
    Runway 12/30 is a primary paved runway at Albuquerque International Sunport used for commercial and general aviation takeoffs and landings.
  • C. Runway 12/30
    Runway 12/30 is a primary paved runway at Minden–Tahoe Airport in Nevada, used for general aviation and glider operations.
  • D. Runway 12/30
    Runway 12/30 is a primary paved runway at Tri-Cities Airport in Tennessee, used for handling a range of commercial and general aviation aircraft operations.
  • E. Runway 12/30
    Runway 12/30 is a principal paved runway at Brest Airport in France, aligned roughly southeast–northwest to accommodate prevailing winds and commercial air traffic.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Runway 12/30
Triple: [KOFF, hasRunway, Runway 12/30]
Generated description
Runway 12/30 is a primary paved runway at KOFF (Offutt Air Force Base) used for military and associated air operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 12/30
Target entity description: Runway 12/30 is a primary paved runway at KOFF (Offutt Air Force Base) used for military and associated air operations.
  • A. Runway 12/30
    Runway 12/30 is a primary paved runway at Garden City Regional Airport in Kansas, used for handling the airport’s commercial and general aviation traffic.
  • B. Runway 12/30
    Runway 12/30 is a primary paved runway at Appleton International Airport used for handling a range of commercial and general aviation aircraft operations.
  • C. Runway 12/30
    Runway 12/30 is a primary paved runway at Edmonton International Airport used for handling a wide range of commercial and general aviation traffic.
  • D. Runway 12/30
    Runway 12/30 is a primary paved runway at Decatur Airport in Illinois, used for handling a range of general aviation and commercial aircraft operations.
  • E. Runway 12/30
    Runway 12/30 is a primary paved runway at Albuquerque International Sunport used for commercial and general aviation takeoffs and landings.
  • F. None of above. chosen

Provenance (5 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_69da627770948190997f486f9a2e370f completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e664365ad0819089103b00d1cf8c9f completed April 20, 2026, 5:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a085a0cc52c8190ac27180a9d86bba7 completed May 16, 2026, 11:50 a.m.
NEDg Description generation batch_6a085ac5b5f4819083c4d12e9cabc758 completed May 16, 2026, 11:53 a.m.
NED2 Entity disambiguation (via description) batch_6a085bc0781c81909fc53a83291badc0 completed May 16, 2026, 11:57 a.m.
Created at: April 11, 2026, 3:39 p.m.