Triple
T15465028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ditton Marsh |
E372008
|
entity |
| Predicate | hasOffPeakFrequency |
P114667
|
FINISHED |
| Object | typically 4 trains per hour to London Waterloo |
—
|
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: typically 4 trains per hour to London Waterloo | Statement: [Ditton Marsh, hasOffPeakFrequency, typically 4 trains per hour to London Waterloo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOffPeakFrequency Context triple: [Ditton Marsh, hasOffPeakFrequency, typically 4 trains per hour to London Waterloo]
-
A.
hasPeakOffPeakDifferentiation
Indicates that there is a distinction between peak and off-peak periods in how something is applied, priced, or operated.
-
B.
offPeakServiceFrequency_minutes
chosen
Indicates the number of minutes between successive services during off-peak periods.
-
C.
hasPeakHourFrequency
Indicates how often a service or event occurs during designated peak hours.
-
D.
isOnPeak
Indicates that one entity is located at, or positioned on, the highest point or summit of another entity.
-
E.
hasPeakHourFunction
Indicates that something performs a specific role or behavior during peak hours of activity or usage.
- 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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f680cec8190836a5ec841dee224 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded284bd008190b31c53b4f1cebadd |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:33 a.m.