Triple
T33885263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thames Ditton railway station |
E868611
|
entity |
| Predicate | typicalOffPeakServiceToHamptonCourt |
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: [Thames Ditton railway station, typicalOffPeakServiceToHamptonCourt, 2 trains per hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffPeakServiceToHamptonCourt Context triple: [Thames Ditton railway station, typicalOffPeakServiceToHamptonCourt, 2 trains per hour]
-
A.
typicalOffPeakFrequencyToHastings
Indicates how often, during typical off-peak times, a service or connection operates to Hastings.
-
B.
typicalOffPeakServiceTo
chosen
Indicates the usual or standard off-peak (non-peak time) service pattern that operates to a given destination.
-
C.
hasOffPeakUsage
Indicates that an entity exhibits or is associated with usage occurring during designated off-peak times rather than standard peak periods.
-
D.
offPeakServiceFrequency_minutes
Indicates the number of minutes between successive services during off-peak periods.
-
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_69f34996761c8190864e42f7c9cf215b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:48 a.m.