Triple

T2843165
Position Surface form Disambiguated ID Type / Status
Subject Boston Logan International Airport E62516 entity
Predicate hasRunway P105 FINISHED
Object 4R/22L
4R/22L is a primary paved runway at Boston Logan International Airport used for commercial air traffic operations.
E303550 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: 4R/22L | Statement: [Boston Logan International Airport, hasRunway, 4R/22L]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: 4R/22L
Context triple: [Boston Logan International Airport, hasRunway, 4R/22L]
  • A. R-4
    The R-4 is a World War II–era Sikorsky helicopter recognized as the first mass-produced helicopter and the first to be used operationally by the U.S. military.
  • B. 12R/30L
    12R/30L is a primary paved runway at St. Louis Lambert International Airport used for aircraft takeoffs and landings.
  • C. 10R/28L
    10R/28L is a primary east–west runway at Fort Lauderdale–Hollywood International Airport used for commercial air traffic operations.
  • D. R4
    R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. 13R/31L
    13R/31L is a major runway at Dallas/Fort Worth International Airport used for handling high volumes of 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: 4R/22L
Triple: [Boston Logan International Airport, hasRunway, 4R/22L]
Generated description
4R/22L is a primary paved runway at Boston Logan International Airport used for commercial air traffic operations.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: 4R/22L
Target entity description: 4R/22L is a primary paved runway at Boston Logan International Airport used for commercial air traffic operations.
  • A. R-4
    The R-4 is a World War II–era Sikorsky helicopter recognized as the first mass-produced helicopter and the first to be used operationally by the U.S. military.
  • B. 12R/30L
    12R/30L is a primary paved runway at St. Louis Lambert International Airport used for aircraft takeoffs and landings.
  • C. 10R/28L
    10R/28L is a primary east–west runway at Fort Lauderdale–Hollywood International Airport used for commercial air traffic operations.
  • D. R4
    R4 is a government office building in Oslo that forms part of Norway’s central Regjeringskvartalet complex.
  • E. 13R/31L
    13R/31L is a major runway at Dallas/Fort Worth International Airport used for handling high volumes of commercial air traffic.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf1898748190b031a2bd2091c0c0 completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8d570388190b4ed81ace605c6c3 completed March 10, 2026, 9:48 a.m.
NEDg Description generation batch_69afe9ba068881908727c82d5eddb974 completed March 10, 2026, 9:51 a.m.
NED2 Entity disambiguation (via description) batch_69b00412e7448190898050f18f64ea9a completed March 10, 2026, 11:44 a.m.
Created at: March 6, 2026, 10:01 p.m.