Triple
T32601570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lukla Airport |
E833388
|
entity |
| Predicate | runwaySlope |
P75082
|
FINISHED |
| Object | significant uphill gradient |
—
|
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: significant uphill gradient | Statement: [Lukla Airport, runwaySlope, significant uphill gradient]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwaySlope Context triple: [Lukla Airport, runwaySlope, significant uphill gradient]
-
A.
runwaySurface
Indicates the type or condition of the surface material that a runway is made of or covered with.
-
B.
runway
Indicates a relationship where a runway serves as the takeoff and landing surface used by aircraft at an airport or airfield.
-
C.
runwayPerformance
Indicates the performance characteristics or behavior of an entity (such as an aircraft or vehicle) when operating on a runway, including factors like acceleration, deceleration, and required distances.
-
D.
runwayCharacteristic
chosen
Indicates a relationship where specific attributes or features are associated with a runway.
-
E.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
- 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_69f3492ab63c8190aec24d5003b47c29 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: May 1, 2026, 1:05 a.m.