Triple
T6694425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bogston railway station |
E152711
|
entity |
| Predicate | typicalServiceFrequencyWeekday |
P55256
|
FINISHED |
| Object | every 30 minutes each way |
—
|
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 30 minutes each way | Statement: [Bogston railway station, typicalServiceFrequencyWeekday, every 30 minutes each way]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalServiceFrequencyWeekday Context triple: [Bogston railway station, typicalServiceFrequencyWeekday, every 30 minutes each way]
-
A.
serviceFrequencyType
chosen
Indicates how often a service occurs or is scheduled within a given time period.
-
B.
serviceFrequencyContext
Indicates the contextual conditions or circumstances under which a service’s frequency is defined, applied, or interpreted.
-
C.
typicalSchedule
Indicates the usual or standard timing and sequence of activities or events associated with an entity.
-
D.
typicalEventDay
Indicates the day on which an event is normally or most commonly held or occurs.
-
E.
typicalTimes
Indicates the usual or characteristic times at which an event, activity, or condition typically occurs.
- 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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cd0fa5188190a23281cb09d98139 |
completed | March 27, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0d3c1081908dadff7a6a054123 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:05 p.m.