Triple
T13902868
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Macon Downtown Airport |
E334271
|
entity |
| Predicate | hasFAAcode |
P420
|
FINISHED |
| Object |
MAC
MAC is the FAA airport code for Macon Downtown Airport, a public airport serving Macon, Georgia.
|
E334271
|
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: MAC | Statement: [Macon Downtown Airport, hasFAAcode, MAC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MAC Context triple: [Macon Downtown Airport, hasFAAcode, MAC]
-
A.
MAC
The MAC is a regional museum in Spokane, Washington, featuring art, history, and cultural exhibits focused on the Inland Northwest.
-
B.
MAC
MAC is the common abbreviation for the Macon Bacon, a collegiate summer baseball team based in Macon, Georgia.
-
C.
MAC
The Mid-American Conference (MAC) is a collegiate athletic conference in the United States that sponsors NCAA Division I sports, primarily among universities in the Midwest.
-
D.
MAC
MAC is the commonly used abbreviation for the United Kingdom’s Migration Advisory Committee, an independent body that advises the government on immigration policy.
-
E.
MAC
MAC is the stock ticker symbol for The Macerich Company, a real estate investment trust specializing in shopping centers and retail properties in the United States.
- 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: MAC Triple: [Macon Downtown Airport, hasFAAcode, MAC]
Generated description
MAC is the FAA airport code for Macon Downtown Airport, a public airport serving Macon, Georgia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MAC Target entity description: MAC is the FAA airport code for Macon Downtown Airport, a public airport serving Macon, Georgia.
-
A.
MAC
chosen
MAC is the IATA airport code for Macon Downtown Airport, a public airport serving the city of Macon, Georgia, in the United States.
-
B.
MAC
MAC is the common abbreviation for the Macon Bacon, a collegiate summer baseball team based in Macon, Georgia.
-
C.
MAC
MAC is the common abbreviation for the Macon Mayhem, a professional minor league ice hockey team based in Macon, Georgia.
-
D.
MAC
MAC is the commonly used abbreviation for the Mid-Atlantic Center for the Arts & Humanities, a cultural organization dedicated to preserving and promoting the historic and artistic heritage of the Mid-Atlantic region.
-
E.
MAC
MAC is the stock ticker symbol for The Macerich Company, a real estate investment trust specializing in shopping centers and retail properties in the United States.
- F. None of above.
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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de25db1e308190aaed6a21e443cc44 |
completed | April 14, 2026, 11:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce7638a88190aae1b59c00ee27ce |
completed | May 3, 2026, 10:38 p.m. |
| NEDg | Description generation | batch_69f9fd56da288190b2bd33bc496c3fb9 |
completed | May 5, 2026, 2:23 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fb039fdb1c8190ad5286d1cfe80a29 |
completed | May 6, 2026, 9:02 a.m. |
Created at: April 9, 2026, 10:16 p.m.