Triple
T2572327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UP Express at Union Station |
E57691
|
entity |
| Predicate | serviceFrequencyPeak |
P27955
|
FINISHED |
| Object | every 15 minutes (typical) |
—
|
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: every 15 minutes (typical) | Statement: [UP Express at Union Station, serviceFrequencyPeak, every 15 minutes (typical)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceFrequencyPeak Context triple: [UP Express at Union Station, serviceFrequencyPeak, every 15 minutes (typical)]
-
A.
usagePeak
Indicates that the usage or consumption of something reaches its highest level or intensity during a particular time or condition.
-
B.
hasPeakHourService
chosen
Indicates that a service operates or is available during designated peak or high-demand hours.
-
C.
visitorFrequency
Indicates how often a visitor comes to or interacts with a particular entity or location.
-
D.
laterFrequency
Indicates that one event, state, or action occurs with a lower frequency than another in a temporal sequence.
-
E.
peakDayAttendance
Indicates the number of attendees present on the single highest-attendance day within a given period or event.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3853c848190970e8a2da16d726d |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.