Triple
T12803257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Niagara Falls International Airport |
E306077
|
entity |
| Predicate | ICAOcode |
P419
|
FINISHED |
| Object |
KIAG
KIAG is the ICAO airport code for Niagara Falls International Airport, a public airport serving the Niagara Falls region in New York, United States.
|
E1004576
|
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: KIAG | Statement: [Niagara Falls International Airport, ICAOcode, KIAG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KIAG Context triple: [Niagara Falls International Airport, ICAOcode, KIAG]
-
A.
KAG
KAG is the abbreviation for "Keep America Great," a political campaign slogan associated with Donald Trump.
-
B.
KIAD
KIAD is the ICAO airport code for Washington Dulles International Airport, a major international air travel hub serving the Washington, D.C. metropolitan area.
-
C.
KI
KI is the abbreviation for the Karolinska Institute, a renowned Swedish medical university known for its leading research and role in selecting Nobel laureates in Physiology or Medicine.
-
D.
KI
KI is the vehicle registration code used on license plates for the German city of Kiel.
-
E.
KI
KI is the regional vehicle registration code used on license plates to identify vehicles registered in Kyiv Oblast, Ukraine.
- 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: KIAG Triple: [Niagara Falls International Airport, ICAOcode, KIAG]
Generated description
KIAG is the ICAO airport code for Niagara Falls International Airport, a public airport serving the Niagara Falls region in New York, United States.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KIAG Target entity description: KIAG is the ICAO airport code for Niagara Falls International Airport, a public airport serving the Niagara Falls region in New York, United States.
-
A.
KAG
KAG is the abbreviation for "Keep America Great," a political campaign slogan associated with Donald Trump.
-
B.
KIAD
KIAD is the ICAO airport code for Washington Dulles International Airport, a major international air travel hub serving the Washington, D.C. metropolitan area.
-
C.
KI
KI is the abbreviation for the Karolinska Institute, a renowned Swedish medical university known for its leading research and role in selecting Nobel laureates in Physiology or Medicine.
-
D.
KI
KI is the vehicle registration code used on license plates for the German city of Kiel.
-
E.
KI
KI is the regional vehicle registration code used on license plates to identify vehicles registered in Kyiv Oblast, Ukraine.
- 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_69d7bdf366888190a8cccb982606889c |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96e7e3be48190ba9159c9f1ac2ccd |
completed | April 10, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f68ec463f08190822e5235362cf584 |
completed | May 2, 2026, 11:54 p.m. |
| NEDg | Description generation | batch_69f6908cb8ec8190855b217c13a51f16 |
completed | May 3, 2026, 12:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6917688508190ae5a64494eaadce7 |
completed | May 3, 2026, 12:06 a.m. |
Created at: April 9, 2026, 5:30 p.m.