Triple
T10443453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw suburban rail services |
E246224
|
entity |
| Predicate | peakHourFrequency |
P90998
|
FINISHED |
| Object | high frequency on core corridors |
—
|
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: high frequency on core corridors | Statement: [Warsaw suburban rail services, peakHourFrequency, high frequency on core corridors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: peakHourFrequency Context triple: [Warsaw suburban rail services, peakHourFrequency, high frequency on core corridors]
-
A.
peakHours
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
-
B.
typicalFrequencyWeekdayDaytime
chosen
Indicates the usual or most common frequency with which something occurs during daytime hours on weekdays.
-
C.
populationPeakPeriod
Indicates the time period during which a population reached its highest recorded level.
-
D.
peakDayAttendance
Indicates the number of attendees present on the single highest-attendance day within a given period or event.
-
E.
peakDay
Indicates the specific day on which a quantity, activity, or effect reaches its maximum level within a given 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe083cd881909d2d8ad75d1d94cb |
completed | April 7, 2026, 12:52 p.m. |
| PD | Predicate disambiguation | batch_69d4fb73a5e48190a8df4775bc5da80f |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:15 p.m.