Triple
T4991324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arlanda Express |
E112135
|
entity |
| Predicate | typicalJourneyTime |
P46906
|
FINISHED |
| Object | about 18 minutes |
—
|
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: about 18 minutes | Statement: [Arlanda Express, typicalJourneyTime, about 18 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalJourneyTime Context triple: [Arlanda Express, typicalJourneyTime, about 18 minutes]
-
A.
travelTimeTypical
chosen
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
B.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
C.
hasApproximateWalkingTimeTo
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
-
D.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
E.
previousTravelTimeOnRoute
Indicates the duration of travel that occurred earlier on the same route before the current segment or time period.
- 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_69bd441be7bc8190b530362d427b97d2 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74249a8c8190952680aee06a9286 |
completed | March 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69bd71492dec8190af4c27a3043b35cc |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:34 p.m.