Triple
T17642242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rayleigh railway station |
E429260
|
entity |
| Predicate | typicalOffPeakService |
P80227
|
FINISHED |
| Object | 2 trains per hour to London Liverpool Street |
—
|
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 to London Liverpool Street | Statement: [Rayleigh railway station, typicalOffPeakService, 2 trains per hour to London Liverpool Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffPeakService Context triple: [Rayleigh railway station, typicalOffPeakService, 2 trains per hour to London Liverpool Street]
-
A.
typicalOffPeakServiceTo
chosen
Indicates the usual or standard off-peak (non-peak time) service pattern that operates to a given destination.
-
B.
offPeakServicePattern
Indicates the service pattern or schedule that applies during off-peak (non-rush-hour) times.
-
C.
offPeakServiceFrequency_minutes
Indicates the number of minutes between successive services during off-peak periods.
-
D.
hasOffPeakUsage
Indicates that an entity exhibits or is associated with usage occurring during designated off-peak times rather than standard peak periods.
-
E.
hasPeakOffPeakDifferentiation
Indicates that there is a distinction between peak and off-peak periods in how something is applied, priced, or operated.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46de645208190a40dcf443f8afd82 |
completed | April 19, 2026, 5:53 a.m. |
| PD | Predicate disambiguation | batch_69e3cddc87188190ac2f049b86038676 |
completed | April 18, 2026, 6:30 p.m. |
Created at: April 10, 2026, 6:03 a.m.