Triple
T15292396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | VAL |
E365558
|
entity |
| Predicate | typicalHeadway |
P20359
|
FINISHED |
| Object | as low as 60 to 90 seconds |
—
|
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: as low as 60 to 90 seconds | Statement: [VAL, typicalHeadway, as low as 60 to 90 seconds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalHeadway Context triple: [VAL, typicalHeadway, as low as 60 to 90 seconds]
-
A.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
B.
travelTimeTypical
Indicates the usual or expected amount of time it takes to travel between two locations under normal conditions.
-
C.
transitFrequencyApprox
chosen
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
D.
typicalPeriod
Indicates the usual or characteristic time interval or duration associated with an event, process, or state.
-
E.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03680b60c8190a3ea54a9d34c8105 |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.