Triple
T34401708
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clovis Municipal Airport |
E882994
|
entity |
| Predicate | runway 04/22 length (feet) |
P6291
|
FINISHED |
| Object | 7200 |
—
|
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: 7200 | Statement: [Clovis Municipal Airport, runway 04/22 length (feet), 7200]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway 04/22 length (feet) Context triple: [Clovis Municipal Airport, runway 04/22 length (feet), 7200]
-
A.
runwayLength
chosen
Indicates the length of a runway associated with an airport or airfield.
-
B.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
C.
runwayInformationAvailableIn
Indicates that information about a runway is available within or through a specified medium, source, or context.
-
D.
runwaySurface
Indicates the type or condition of the surface material that a runway is made of or covered with.
-
E.
runwaysUsableAt
Indicates that certain runways at a location are available and suitable for use (e.g., for takeoff or landing) at a given time or under specified conditions.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 1, 2026, 1:59 a.m.