Triple
T15762802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA Purple Line |
E382139
|
entity |
| Predicate | weekdayRushHourService |
P32739
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [CTA Purple Line, weekdayRushHourService, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weekdayRushHourService Context triple: [CTA Purple Line, weekdayRushHourService, yes]
-
A.
weekdayServicePattern
Indicates a service pattern or schedule that specifically applies on weekdays rather than weekends or holidays.
-
B.
weekdayPeakDirectionService
chosen
Indicates that the service operates primarily during weekday peak travel periods in a specific direction.
-
C.
activityPeakPeriod
Indicates the time period during which an activity reaches its highest level or intensity.
-
D.
dayType
Indicates the classification or category of a given day based on its characteristics or role (e.g., weekday, weekend, holiday).
-
E.
typicalFrequencyWeekdayDaytime
Indicates the usual or most common frequency with which something occurs during daytime hours on weekdays.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b6c9fc8190a1bcf763c4b04b12 |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
Created at: April 10, 2026, 4:47 a.m.