Triple

T15238898
Position Surface form Disambiguated ID Type / Status
Subject Faith Municipal Airport E364201 entity
Predicate hasRunway P105 FINISHED
Object Runway 12/30
Runway 12/30 is a primary aircraft landing and takeoff strip at Faith Municipal Airport in South Dakota.
E1155202 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: [Faith Municipal Airport, hasRunway, Runway 12/30]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Runway 12/30
Context triple: [Faith Municipal Airport, hasRunway, Runway 12/30]
  • A. Runway 12/30
    Runway 12/30 is a principal runway at Cairns Airport in Queensland, Australia, used for both domestic and international aircraft operations.
  • B. Runway 12/30
    Runway 12/30 is a principal paved runway at Ambala Air Force Station in Haryana, India, used for military flight operations.
  • C. 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.
  • D. 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.
  • E. Runway 12/30
    Runway 12/30 is a primary paved runway at Brewton Municipal Airport in Alabama, used for general aviation takeoffs and landings aligned roughly southeast–northwest.
  • 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: [Faith Municipal Airport, hasRunway, Runway 12/30]
Generated description
Runway 12/30 is a primary aircraft landing and takeoff strip at Faith Municipal Airport in South Dakota.
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 aircraft landing and takeoff strip at Faith Municipal Airport in South Dakota.
  • 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 Albuquerque International Sunport used for commercial and general aviation takeoffs and landings.
  • C. 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.
  • D. 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.
  • E. Runway 12/30
    Runway 12/30 is a primary paved runway at Sacramento Executive Airport used for general aviation takeoffs and landings aligned roughly southeast–northwest.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007da7e988190925a9b67b8070bc7 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff133950288190a5ffeb52ee0bac37 completed May 9, 2026, 10:58 a.m.
NEDg Description generation batch_69ff145ac8e081908b075cee67e82aa3 completed May 9, 2026, 11:02 a.m.
NED2 Entity disambiguation (via description) batch_69ff1509e5a48190b69f1a44d793e07d completed May 9, 2026, 11:05 a.m.
Created at: April 10, 2026, 3:12 a.m.