Triple
T13249054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Johns railway station |
E315478
|
entity |
| Predicate | typicalOffPeakFrequencyToLondonCannonStreet |
P80227
|
FINISHED |
| Object | 2 trains per hour |
—
|
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 | Statement: [St Johns railway station, typicalOffPeakFrequencyToLondonCannonStreet, 2 trains per hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffPeakFrequencyToLondonCannonStreet Context triple: [St Johns railway station, typicalOffPeakFrequencyToLondonCannonStreet, 2 trains per hour]
-
A.
typicalOffPeakServiceTo
chosen
Indicates the usual or standard off-peak (non-peak time) service pattern that operates to a given destination.
-
B.
fareZoneFromCentralLondon
Indicates the public transport fare zone in which a location lies, measured relative to central London.
-
C.
typicalFrequencyWeekdayDaytime
Indicates the usual or most common frequency with which something occurs during daytime hours on weekdays.
-
D.
transitFrequencyApprox
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
E.
offPeakServicePattern
Indicates the service pattern or schedule that applies during off-peak (non-rush-hour) times.
- 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_69d806b1072881909e46bd212259c5f0 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98d9e7ea881908abc4b3a54896692 |
completed | April 10, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69d98bcca7d88190a3e68e99ed3a29e6 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:24 p.m.