Triple

T3302986
Position Surface form Disambiguated ID Type / Status
Subject Harbor Springs Municipal Airport E69378 entity
Predicate FAAcode P420 FINISHED
Object MGN
MGN is the FAA airport code for Harbor Springs Municipal Airport, a public-use airfield serving Harbor Springs, Michigan.
 E347636 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: MGN | Statement: [Harbor Springs Municipal Airport, FAAcode, MGN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: MGN
Context triple: [Harbor Springs Municipal Airport, FAAcode, MGN]
  • A. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • B. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • C. MGY
    MGY was the distinctive wireless call sign used by the RMS Titanic for its radio communications.
  • D. MG
    MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
  • E. MAG
    MAG is the abbreviated name used to represent Magic Gaming, the NBA 2K League affiliate of the Orlando Magic.
  • 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: MGN
Triple: [Harbor Springs Municipal Airport, FAAcode, MGN]
Generated description
MGN is the FAA airport code for Harbor Springs Municipal Airport, a public-use airfield serving Harbor Springs, Michigan.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: MGN
Target entity description: MGN is the FAA airport code for Harbor Springs Municipal Airport, a public-use airfield serving Harbor Springs, Michigan.
  • A. MGA
    MGA is a public university in Georgia, United States, offering a range of undergraduate and graduate programs across multiple campuses.
  • B. MGA
    MGA is the commonly used abbreviation for the Maryland General Assembly, the state’s bicameral legislative body.
  • C. MGY
    MGY was the distinctive wireless call sign used by the RMS Titanic for its radio communications.
  • D. MG
    MG is a historic British automotive marque best known for its sports cars, now owned and produced by Chinese manufacturer SAIC Motor.
  • E. MAG
    MAG is the abbreviated name used to represent Magic Gaming, the NBA 2K League affiliate of the Orlando Magic.
  • 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_69ad859e529c8190a404273f53cb487d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0c662308190aad8b2a93e1c8a5c completed March 8, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2f3e383088190a056ca793ebf4ffe completed March 12, 2026, 5:12 p.m.
NEDg Description generation batch_69b2f9fb060881909dd940c69cf4a12e completed March 12, 2026, 5:38 p.m.
NED2 Entity disambiguation (via description) batch_69b3137bf988819080cef6c1946ec622 completed March 12, 2026, 7:26 p.m.
Created at: March 8, 2026, 3:11 p.m.