Triple
T36816769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maho Beach |
E909762
|
entity |
| Predicate | runwayThresholdDistance |
P188487
|
FINISHED |
| Object | very close to runway threshold |
—
|
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: very close to runway threshold | Statement: [Maho Beach, runwayThresholdDistance, very close to runway threshold]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runwayThresholdDistance Context triple: [Maho Beach, runwayThresholdDistance, very close to runway threshold]
-
A.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
B.
runwayEnd
Indicates that one entity represents the end point or terminus of a runway associated with the other entity.
-
C.
runwayLength
Indicates the length of a runway associated with an airport or airfield.
-
D.
runwayCharacteristic
Indicates a relationship where specific attributes or features are associated with a runway.
-
E.
runwaySurface
Indicates the type or condition of the surface material that a runway is made of or covered with.
- 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_69f76e7dd13c81908c60b05adb49eeb5 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fba78aca4c8190b8f1831e8cc04e06 |
completed | May 6, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69fba34a65a4819088bac6c17542d71c |
completed | May 6, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69fba789c1188190973a919bfe2871f3 |
completed | May 6, 2026, 8:41 p.m. |
Created at: May 3, 2026, 4:13 p.m.