Triple
T35541301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helen's Bay railway station |
E1027067
|
entity |
| Predicate | serviceFrequencySaturdays |
P55256
|
FINISHED |
| Object | half-hourly in 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: half-hourly in each direction | Statement: [Helen's Bay railway station, serviceFrequencySaturdays, half-hourly in each direction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceFrequencySaturdays Context triple: [Helen's Bay railway station, serviceFrequencySaturdays, half-hourly in each direction]
-
A.
serviceFrequencyEveningSunday
Indicates how often a service operates during Sunday evening hours.
-
B.
serviceFrequencyType
chosen
Indicates how often a service occurs or is scheduled within a given time period.
-
C.
serviceFrequencyContext
Indicates the contextual conditions or circumstances under which a service’s frequency is defined, applied, or interpreted.
-
D.
typicalFrequencySunday
Indicates how frequently an event, action, or relationship typically occurs on Sundays.
-
E.
weekendService
Indicates that a service, operation, or activity is provided or occurs specifically on weekends.
- 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_69f76e008ba08190927acd8e5e0344c8 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd57ba740c8190bd1d40166fccccb7 |
completed | May 8, 2026, 3:25 a.m. |
| PD | Predicate disambiguation | batch_69fd55ee82b881908a639da3a41b3af6 |
completed | May 8, 2026, 3:18 a.m. |
Created at: May 3, 2026, 4:04 p.m.