Triple
T3843003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orlando Executive Airport |
E93498
|
entity |
| Predicate | ICAOCode |
P419
|
FINISHED |
| Object |
KORL
KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
|
E392406
|
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: KORL | Statement: [Orlando Executive Airport, ICAOCode, KORL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KORL Context triple: [Orlando Executive Airport, ICAOCode, KORL]
-
A.
kora
The kora is a West African 21-string harp-lute traditionally played by griots and widely associated with the musical heritage of Mali.
-
B.
KORD
KORD is the ICAO airport code for Chicago O'Hare International Airport, one of the busiest and most significant air transport hubs in the United States.
-
C.
Kors
Kors is the surname of American fashion designer Michael Kors, known for his eponymous luxury brand.
-
D.
KALO
KALO is the ICAO airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
-
E.
KAL
KAL is the ICAO airline designator used to identify Korean Air in international aviation operations.
- 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: KORL Triple: [Orlando Executive Airport, ICAOCode, KORL]
Generated description
KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KORL Target entity description: KORL is the ICAO airport code for Orlando Executive Airport, a public airport serving the Orlando, Florida area.
-
A.
kora
The kora is a West African 21-string harp-lute traditionally played by griots and widely associated with the musical heritage of Mali.
-
B.
KORD
KORD is the ICAO airport code for Chicago O'Hare International Airport, one of the busiest and most significant air transport hubs in the United States.
-
C.
Kors
Kors is the surname of American fashion designer Michael Kors, known for his eponymous luxury brand.
-
D.
KALO
KALO is the ICAO airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
-
E.
KAL
KAL is the ICAO airline designator used to identify Korean Air in international aviation operations.
- 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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb397ac81908f74a42a0eeb8682 |
completed | March 9, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5040f93948190b104cf1b7db671b7 |
completed | March 14, 2026, 6:45 a.m. |
| NEDg | Description generation | batch_69b504c46dcc8190a9775c39e5c734a9 |
completed | March 14, 2026, 6:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b505742830819093a861bde17c03c0 |
completed | March 14, 2026, 6:51 a.m. |
Created at: March 9, 2026, 3:18 p.m.