Triple
T24363683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Runway 15/33 |
E614133
|
entity |
| Predicate | hasIcaoAirport |
P155924
|
FINISHED |
| Object | LOWS |
—
|
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: LOWS | Statement: [Runway 15/33, hasIcaoAirport, LOWS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIcaoAirport Context triple: [Runway 15/33, hasIcaoAirport, LOWS]
-
A.
isCivilAirport
Indicates that an airport is designated and used primarily for civilian (non-military) aviation operations.
-
B.
hasICAOComplement
Indicates that one entity serves as an ICAO-standard complement or additional code/information corresponding to another entity’s primary ICAO designation.
-
C.
hasIATAcode
Indicates that an entity, typically a transportation facility like an airport, is associated with a specific IATA (International Air Transport Association) code.
-
D.
ICAOairport
Indicates that an entity is an airport identified or classified according to the ICAO (International Civil Aviation Organization) airport coding system.
-
E.
ICAOcode
Indicates that an entity is identified by a specific four-letter airport or aerodrome code assigned by the International Civil Aviation Organization (ICAO).
- F. None of above. chosen
Provenance (4 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_69e2d7dfe7f08190b7a1f3a36483ab05 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2938694548190a3fcb148cfff65b0 |
completed | April 29, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f287bb1b2c81909c2e7fcc392ad143 |
completed | April 29, 2026, 10:35 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:01 a.m.