Triple
T36996302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkswell railway station |
E915236
|
entity |
| Predicate | typicalOffPeakFrequencyToCoventry |
P205686
|
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: [Berkswell railway station, typicalOffPeakFrequencyToCoventry, 2 trains per hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffPeakFrequencyToCoventry Context triple: [Berkswell railway station, typicalOffPeakFrequencyToCoventry, 2 trains per hour]
-
A.
typicalOffPeakFrequencyToHastings
Indicates how often, during typical off-peak times, a service or connection operates to Hastings.
-
B.
offPeakServiceFrequency_minutes
Indicates the number of minutes between successive services during off-peak periods.
-
C.
typicalOffPeakServiceTo
Indicates the usual or standard off-peak (non-peak time) service pattern that operates to a given destination.
-
D.
typicalOffPeakTrainsPerHourToLondonWaterloo
Indicates the usual number of trains per hour running to London Waterloo during off-peak times.
-
E.
typicalFrequencyWeekdayDaytime
Indicates the usual or most common frequency with which something occurs during daytime hours on weekdays.
- 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_69f76e8f1a8c81909db172ed31304971 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:14 p.m.