Triple
T36897083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RAE West Freugh |
E911918
|
entity |
| Predicate | hasAirfieldCodeType |
P7891
|
FINISHED |
| Object | RAF station |
—
|
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: RAF station | Statement: [RAE West Freugh, hasAirfieldCodeType, RAF station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirfieldCodeType Context triple: [RAE West Freugh, hasAirfieldCodeType, RAF station]
-
A.
hasAirfieldType
Indicates that an airfield is classified as having a particular type or category of airfield.
-
B.
hasAirportCodeType
chosen
Indicates that an airport code is associated with a specific classification or type (e.g., IATA, ICAO, FAA).
-
C.
containsAirfield
Indicates that a location or area includes at least one airfield within its boundaries.
-
D.
airfieldCode
Indicates that an entity is identified by a specific airfield code used to uniquely reference that airfield.
-
E.
hasIcaoAirport
Indicates that an entity is associated with an airport identified by a specific ICAO (International Civil Aviation Organization) airport 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_69f76e841b54819097e7fa768bbc70b2 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f9fd90b15c8190801dffdc65d39c78 |
completed | May 5, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69f7cf79ddb08190a083405cccc14137 |
completed | May 3, 2026, 10:43 p.m. |
Created at: May 3, 2026, 4:13 p.m.