Triple
T25546570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nairobi–Lusaka |
E640322
|
entity |
| Predicate | hasIATACodeAtDestination |
P2569
|
FINISHED |
| Object | LUN |
—
|
NE NERFINISHED |
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: LUN | Statement: [Nairobi–Lusaka, hasIATACodeAtDestination, LUN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIATACodeAtDestination Context triple: [Nairobi–Lusaka, hasIATACodeAtDestination, LUN]
-
A.
usesIATACodeAtOtherEnd
Indicates that one entity identifies or refers to the other end of a route, connection, or relationship using its IATA airport code.
-
B.
hasIATAcode
chosen
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
-
C.
hasIATAStyle
Indicates that one entity uses or conforms to the IATA (International Air Transport Association) style or formatting standard associated with another entity.
-
D.
hasIATAFlightNumber
Indicates that an entity (typically a flight) is associated with a specific IATA-designated flight number.
-
E.
associatedWithIATATypeCode
Indicates that one entity is linked to or characterized by a specific IATA type code that classifies its role or function in air transport.
- F. None of above.
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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8992ce881909b95d520f580e231 |
completed | May 2, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69f480789be08190ab252a6de3797200 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 3:34 p.m.