Triple
T5967913
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegheny County Airport |
E132798
|
entity |
| Predicate | ICAO code |
P419
|
FINISHED |
| Object |
KAGC
KAGC is the ICAO airport code for Allegheny County Airport, a public airport serving the Pittsburgh, Pennsylvania area.
|
E559397
|
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: KAGC | Statement: [Allegheny County Airport, ICAO code, KAGC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KAGC Context triple: [Allegheny County Airport, ICAO code, KAGC]
-
A.
KAG
KAG is the abbreviation for "Keep America Great," a political campaign slogan associated with Donald Trump.
-
B.
KAGS
KAGS is the ICAO airport code for Augusta Regional Airport, a public airport serving the Augusta, Georgia area in the United States.
-
C.
KCGS
KCGS is the ICAO airport code for College Park Airport, a historic general aviation airfield located in College Park, Maryland, USA.
-
D.
KCA
KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
-
E.
KGN
KGN is the standard three-letter abbreviation used for the Kingston Frontenacs, a major junior ice hockey team in the Ontario Hockey League.
- 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: KAGC Triple: [Allegheny County Airport, ICAO code, KAGC]
Generated description
KAGC is the ICAO airport code for Allegheny County Airport, a public airport serving the Pittsburgh, Pennsylvania area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KAGC Target entity description: KAGC is the ICAO airport code for Allegheny County Airport, a public airport serving the Pittsburgh, Pennsylvania area.
-
A.
KAG
KAG is the abbreviation for "Keep America Great," a political campaign slogan associated with Donald Trump.
-
B.
KAGS
KAGS is the ICAO airport code for Augusta Regional Airport, a public airport serving the Augusta, Georgia area in the United States.
-
C.
KCGS
KCGS is the ICAO airport code for College Park Airport, a historic general aviation airfield located in College Park, Maryland, USA.
-
D.
KCA
KCA is a nonprofit organization dedicated to providing life-saving HIV treatment, care, and support to children and families in underserved communities, particularly in Africa and India.
-
E.
KGN
KGN is the standard three-letter abbreviation used for the Kingston Frontenacs, a major junior ice hockey team in the Ontario Hockey League.
- 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_69c0086deab081908550159ca23eec9b |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03a3f612481908744cb645f2ede1d |
completed | March 22, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3ff62f08190be56bb9c450c9647 |
completed | March 23, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69c0f61d80808190913b425c3c57f990 |
completed | March 23, 2026, 8:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0f6a75b908190b35d13b9593cf21f |
completed | March 23, 2026, 8:15 a.m. |
Created at: March 22, 2026, 4:03 p.m.