Triple
T13248605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clock House |
E315468
|
entity |
| Predicate | typicalOffPeakFrequencyToLondon |
P90998
|
FINISHED |
| Object | 4 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: 4 trains per hour | Statement: [Clock House, typicalOffPeakFrequencyToLondon, 4 trains per hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffPeakFrequencyToLondon Context triple: [Clock House, typicalOffPeakFrequencyToLondon, 4 trains per hour]
-
A.
typicalOffPeakServiceTo
Indicates the usual or standard off-peak (non-peak time) service pattern that operates to a given destination.
-
B.
typicalFrequencyWeekdayDaytime
chosen
Indicates the usual or most common frequency with which something occurs during daytime hours on weekdays.
-
C.
hasPeakOffPeakDifferentiation
Indicates that there is a distinction between peak and off-peak periods in how something is applied, priced, or operated.
-
D.
typicalOffsetWinter
Indicates the usual temporal or spatial offset associated with winter in relation to a reference point or period.
-
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.