Triple

T10892761
Position Surface form Disambiguated ID Type / Status
Subject PNS E257222 entity
Predicate hasRunway P105 FINISHED
Object Runway 17/35
Runway 17/35 is a primary paved runway at Pensacola Naval Air Station used for military aircraft operations.
 E926706 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 17/35 | Statement: [PNS, hasRunway, Runway 17/35]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 17/35
Context triple: [PNS, hasRunway, Runway 17/35]
  • A. Runway 17/35
    Runway 17/35 is a primary paved runway used for aircraft operations at Kauhava Air Base in Finland.
  • B. Runway 17/35
    Runway 17/35 is a primary paved runway at Fort Worth Meacham International Airport used for general aviation and regional air traffic operations.
  • C. Runway 17/35
    Runway 17/35 is a primary paved runway at Essendon Airport in Melbourne, Australia, used for a mix of general aviation, corporate, and regional aircraft operations.
  • D. Runway 17/35
    Runway 17/35 is a primary paved runway at Bergen Airport, Flesland in Norway, used for both domestic and international air traffic operations.
  • E. Runway 17/35
    Runway 17/35 is one of the primary paved runways at Minneapolis–Saint Paul International Airport, used for both commercial and general aviation operations.
  • 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 17/35
Triple: [PNS, hasRunway, Runway 17/35]
Generated description
Runway 17/35 is a primary paved runway at Pensacola Naval Air Station used for military aircraft operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Runway 17/35
Target entity description: Runway 17/35 is a primary paved runway at Pensacola Naval Air Station used for military aircraft operations.
  • A. Runway 17/35
    Runway 17/35 is a primary paved runway at Fort Worth Meacham International Airport used for general aviation and regional air traffic operations.
  • B. Runway 17/35
    Runway 17/35 is a primary paved runway at Roswell Air Center in New Mexico, used for commercial, military, and general aviation operations.
  • C. Runway 17/35
    Runway 17/35 is a primary paved runway at Jack Edwards National Airport in Gulf Shores, Alabama, used for general aviation and regional air traffic operations.
  • D. Runway 17/35
    Runway 17/35 is one of the primary paved runways at Minneapolis–Saint Paul International Airport, used for both commercial and general aviation operations.
  • E. Runway 17/35
    Runway 17/35 is a primary paved runway at Grand Forks International Airport used for general aviation, commercial, and training flight operations.
  • 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_69d6aa8550c8819095508a2ed9acf3db completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d75206354881908b148f2df3938513 completed April 9, 2026, 7:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69e5e890bb9c81908c316a6423e650e6 completed April 20, 2026, 8:49 a.m.
NEDg Description generation batch_69e5eeb38d588190b51b6c299bb717dd completed April 20, 2026, 9:15 a.m.
NED2 Entity disambiguation (via description) batch_69e5f19dd3348190b037e09c87b528e9 completed April 20, 2026, 9:27 a.m.
Created at: April 8, 2026, 9:21 p.m.