Triple
T5836563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton-on-Thames railway station |
E129484
|
entity |
| Predicate | typicalOffPeakServiceToLondonWaterloo |
P24204
|
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: [Walton-on-Thames railway station, typicalOffPeakServiceToLondonWaterloo, 4 trains per hour]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalOffPeakServiceToLondonWaterloo Context triple: [Walton-on-Thames railway station, typicalOffPeakServiceToLondonWaterloo, 4 trains per hour]
-
A.
primaryLondonTerminal
Indicates that a given station serves as the main London terminal for a particular rail service or route.
-
B.
secondaryLondonTerminal
Indicates that a location serves as a secondary terminal in London associated with a primary London terminal for a given service or route.
-
C.
servesCentralLondon
Indicates that something provides service or access specifically to the Central London area.
-
D.
typicalOffsetWinter
Indicates the usual temporal or spatial offset associated with winter in relation to a reference point or period.
-
E.
offPeakServicePattern
chosen
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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.