Triple
T4504128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegro |
E101290
|
entity |
| Predicate | travelTimeBetweenTermini |
P46906
|
FINISHED |
| Object | about 3.5 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: about 3.5 hours | Statement: [Allegro, travelTimeBetweenTermini, about 3.5 hours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelTimeBetweenTermini Context triple: [Allegro, travelTimeBetweenTermini, about 3.5 hours]
-
A.
railwayTimeUsage
Indicates how much time is spent using or operating a railway within a given context or period.
-
B.
travelTimeTypical
chosen
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
C.
transitFrequencyApprox
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
D.
travelTimeCategory
Indicates the qualitative classification of how long a given travel or trip duration is (e.g., short, medium, long).
-
E.
hasApproximateWalkingTimeTo
Indicates that there is an estimated or approximate amount of time it takes to walk from one entity to another.
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56fca7d4819081deb34628e04f00 |
completed | March 20, 2026, 2:17 p.m. |
| PD | Predicate disambiguation | batch_69bd521671688190bc655d25fa77eba2 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:01 p.m.