Triple
T9844796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muskegon County Airport |
E239312
|
entity |
| Predicate | hasFAAIdentifier |
P420
|
FINISHED |
| Object | MKG |
E239311
|
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: MKG | Statement: [Muskegon County Airport, hasFAAIdentifier, MKG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MKG Context triple: [Muskegon County Airport, hasFAAIdentifier, MKG]
-
A.
MKG
chosen
MKG is the three-letter IATA airport code for Muskegon County Airport in Muskegon, Michigan, USA.
-
B.
MKT
MKT was the reporting mark and common abbreviation for the Missouri–Kansas–Texas Railroad, a major regional railroad that served the south-central United States.
-
C.
KMKG
KMKG is the ICAO airport code for Muskegon County Airport in Muskegon, Michigan, United States.
-
D.
MGN
MGN is the FAA airport code for Harbor Springs Municipal Airport, a public-use airfield serving Harbor Springs, Michigan.
-
E.
KMK
KMK is the central coordinating body of Germany’s state education and cultural ministers, responsible for harmonizing policies across the federal states.
- 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_69ca84e3f0c48190ada72a65ebd50efd |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb35dc29c819080203be5b904dc9d |
completed | April 2, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1e42edd98819092d07139890d83e4 |
completed | April 5, 2026, 4:25 a.m. |
Created at: March 30, 2026, 8:33 p.m.