Triple
T5344185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aira Force |
E124011
|
entity |
| Predicate | hasApproximateWalkTime |
P53938
|
FINISHED |
| Object | 1 to 2 hours |
—
|
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: 1 to 2 hours | Statement: [Aira Force, hasApproximateWalkTime, 1 to 2 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateWalkTime Context triple: [Aira Force, hasApproximateWalkTime, 1 to 2 hours]
-
A.
hasApproximateWalkingTimeTo
chosen
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
-
B.
endTimeApproximate
Indicates that the recorded end time of an event or action is not exact but an approximate value.
-
C.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
D.
hasStopNear
Indicates that one entity has a stop or stopping point located in close proximity to another entity.
-
E.
approximateHikeTimeRoundTrip
Indicates the estimated total time required to complete a hike from the starting point to the destination and back to the start.
- 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_69bd464be27081908807b40b75c1bbae |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85ea5e748190a9943de794e5c1ec |
completed | March 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69bd845a62b081909782863865b257a9 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:01 p.m.