Triple
T1543553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LUV |
E32924
|
entity |
| Predicate | associatedWithIATA |
P12360
|
FINISHED |
| Object | WN |
—
|
LITERAL FINISHED |
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: WN | Statement: [LUV, associatedWithIATA, WN]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithIATA Context triple: [LUV, associatedWithIATA, WN]
-
A.
associatedWithIATAAirlineCode
chosen
Indicates that an entity is linked to or identified by a specific IATA airline code.
-
B.
associatedAirlineICAOCode
Indicates the ICAO airline code that is linked to or used by the given entity (such as a flight, route, or service).
-
C.
associatedWithAirportName
Indicates a relationship where an entity is linked or connected to a specific airport by its name.
-
D.
associatedWithAirportType
Indicates that an entity has a connection or linkage to a specific category or type of airport.
-
E.
hasIATAcode
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.