Triple
T28733642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kidwelly railway station |
E730732
|
entity |
| Predicate | hasApproximateServiceFrequency |
P20359
|
FINISHED |
| Object | hourly (weekdays, daytime) |
—
|
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: hourly (weekdays, daytime) | Statement: [Kidwelly railway station, hasApproximateServiceFrequency, hourly (weekdays, daytime)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateServiceFrequency Context triple: [Kidwelly railway station, hasApproximateServiceFrequency, hourly (weekdays, daytime)]
-
A.
serviceFrequencyContext
Indicates the contextual conditions or circumstances under which a service’s frequency is defined, applied, or interpreted.
-
B.
serviceFrequencyType
Indicates how often a service occurs or is scheduled within a given time period.
-
C.
hasFrequentServices
Indicates that one entity regularly provides or receives services from another entity at short or recurring intervals.
-
D.
transitFrequencyApprox
chosen
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
E.
isFrequentlyBroadcastDuring
Indicates that one entity (such as a program, advertisement, or message) is regularly aired or transmitted during another entity (such as a specific time slot, event, or show).
- 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_69f043eae0908190b28ce314686247d7 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f7688dd3d08190ad13d0e780570a1c |
completed | May 3, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69f767fcf2f881908bacc7bfc38e68a5 |
completed | May 3, 2026, 3:21 p.m. |
Created at: April 28, 2026, 5:59 a.m.