Triple

T10438793
Position Surface form Disambiguated ID Type / Status
Subject KBOS runway system E246112 entity
Predicate hasRunway P105 FINISHED
Object Runway 14/32 E49358 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: Runway 14/32 | Statement: [KBOS runway system, hasRunway, Runway 14/32]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Runway 14/32
Context triple: [KBOS runway system, hasRunway, Runway 14/32]
  • A. Runway 14/32
    Runway 14/32 is a primary paved runway at Bern Airport in Switzerland, used for both commercial and general aviation operations.
  • B. Runway 14/32
    Runway 14/32 is a primary paved runway at Buffalo Niagara International Airport used for commercial and general aviation takeoffs and landings under varying wind and weather conditions.
  • C. Runway 14/32
    Runway 14/32 is a primary paved runway at Charles M. Schulz–Sonoma County Airport in Santa Rosa, California, used for general aviation and commercial flights.
  • D. Runway 14/32
    Runway 14/32 is a primary paved runway at Kertajati International Airport in West Java, Indonesia, designed to accommodate large commercial aircraft operations.
  • E. Runway 14/32 chosen
    Runway 14/32 is one of the primary paved runways at Boston Logan International Airport, used for handling a mix of domestic and international air traffic under varying wind and weather conditions.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4fb9ba23c81909eac3aea292b2bd3 completed April 7, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69dbd966f0f08190a60ca3bcf0e08e98 completed April 12, 2026, 5:41 p.m.
Created at: April 6, 2026, 12:14 p.m.