Triple

T22817775
Position Surface form Disambiguated ID Type / Status
Subject Mount Cook Aerodrome E565145 entity
Predicate IATAcode P418 FINISHED
Object MON
MON is the IATA airport code for Mount Cook Aerodrome, a small airport serving the Mount Cook region in New Zealand.
 E1556076 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: MON | Statement: [Mount Cook Aerodrome, IATAcode, MON]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MON
Context triple: [Mount Cook Aerodrome, IATAcode, MON]
  • A. MON
    MON is a renowned contemporary art museum in Curitiba, Brazil, celebrated for its striking, futuristic architecture designed by Oscar Niemeyer.
  • B. MON
    MON is the standard abbreviation used for the Montreal Canadiens, the historic National Hockey League team based in Montreal, Quebec.
  • C. MON
    MON is the commonly used abbreviation for Poland’s Ministry of National Defence, the government body responsible for the country’s defense policy and armed forces.
  • D. MON
    MON is the three-letter International Olympic Committee country code representing Monaco in Olympic competitions.
  • E. MON
    MON is the post-nominal abbreviation used to denote recipients of Nigeria’s national honor, the Order of the Niger.
  • 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: MON
Triple: [Mount Cook Aerodrome, IATAcode, MON]
Generated description
MON is the IATA airport code for Mount Cook Aerodrome, a small airport serving the Mount Cook region in New Zealand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MON
Target entity description: MON is the IATA airport code for Mount Cook Aerodrome, a small airport serving the Mount Cook region in New Zealand.
  • A. MON
    MON is the standard abbreviation used for the Montreal Canadiens, the historic National Hockey League team based in Montreal, Quebec.
  • B. MON
    MON is the commonly used abbreviation for Poland’s Ministry of National Defence, the government body responsible for the country’s defense policy and armed forces.
  • C. MON
    MON is the three-letter International Olympic Committee country code representing Monaco in Olympic competitions.
  • D. MON
    MON is the post-nominal abbreviation used to denote recipients of Nigeria’s national honor, the Order of the Niger.
  • E. MON
    MON is a renowned contemporary art museum in Curitiba, Brazil, celebrated for its striking, futuristic architecture designed by Oscar Niemeyer.
  • 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_69e2458426188190b58b8ab4844fe420 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17dcd7da481909d591f145382725b completed April 29, 2026, 3:41 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0b9ea6b87c819088abf95f56014724 completed May 18, 2026, 11:20 p.m.
NEDg Description generation batch_6a0ba271f1548190afa04f8cf4d1da0b completed May 18, 2026, 11:36 p.m.
NED2 Entity disambiguation (via description) batch_6a0ba3b3cb288190a96a23d310c16d52 completed May 18, 2026, 11:41 p.m.
Created at: April 17, 2026, 3:33 p.m.