Triple
T11123682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Seretse Khama International Airport |
E263080
|
entity |
| Predicate | runway08_26LengthMeters |
P6291
|
FINISHED |
| Object | 4000 |
—
|
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: 4000 | Statement: [Sir Seretse Khama International Airport, runway08_26LengthMeters, 4000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runway08_26LengthMeters Context triple: [Sir Seretse Khama International Airport, runway08_26LengthMeters, 4000]
-
A.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
B.
runwayLength
chosen
Indicates the length of a runway associated with an airport or airfield.
-
C.
runwayLengthUnit
Indicates the unit of measurement used to express the length of a runway in the relationship.
-
D.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
E.
runwayEnd
Indicates that one entity represents the end point or terminus of a runway associated with the other entity.
- 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_69d6aa9b46cc8190b19f9f0cc45bf322 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7e82e933481908550499cf9dd6531 |
completed | April 9, 2026, 5:55 p.m. |
| PD | Predicate disambiguation | batch_69d7441efe948190ae4ab020121e169d |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:28 p.m.