Triple
T9874558
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Outwood railway station |
E240040
|
entity |
| Predicate | typicalFrequencyWeekdayDaytime |
P90998
|
FINISHED |
| Object | 2 trains per hour each direction |
—
|
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: 2 trains per hour each direction | Statement: [Outwood railway station, typicalFrequencyWeekdayDaytime, 2 trains per hour each direction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFrequencyWeekdayDaytime Context triple: [Outwood railway station, typicalFrequencyWeekdayDaytime, 2 trains per hour each direction]
-
A.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
B.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
-
C.
peakHours
Indicates that an action, event, or condition occurs during the busiest or most heavily trafficked time period.
-
D.
activityPeakPeriod
Indicates the time period during which an activity reaches its highest level or intensity.
-
E.
typicalPeriod
Indicates the usual or characteristic time interval or duration associated with an event, process, or state.
- F. None of above. chosen
Provenance (4 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_69ca84e8a0788190b9061811d50fd554 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3f89fa081908b58956902c193cf |
completed | April 2, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69cd3581a9688190a00cef4c3eebb0ae |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:37 p.m.