Triple
T20314755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hamburg–Copenhagen |
E510349
|
entity |
| Predicate | typicalTravelTime |
P46906
|
FINISHED |
| Object | approximately 4 hours 30 minutes to 5 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: approximately 4 hours 30 minutes to 5 hours | Statement: [Hamburg–Copenhagen, typicalTravelTime, approximately 4 hours 30 minutes to 5 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTravelTime Context triple: [Hamburg–Copenhagen, typicalTravelTime, approximately 4 hours 30 minutes to 5 hours]
-
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.
bestTravelTime
Indicates the most optimal duration or period required to travel between specified locations under given conditions.
-
D.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
E.
approximateTripDuration
Indicates the estimated length of time required to complete a trip between specified locations or points in a journey.
- 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_69e0b4c7491c8190961113c4283b10b0 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e67786f4dc8190b02a6c2a4338362d |
completed | April 20, 2026, 6:59 p.m. |
| PD | Predicate disambiguation | batch_69e55b21b09081909e46691b6f45a07f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 11:19 a.m.