Triple
T4312797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alton railway station |
E94111
|
entity |
| Predicate | hasDepartureFrequency |
P20359
|
FINISHED |
| Object | typically two 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 two trains per hour to London Waterloo | Statement: [Alton railway station, hasDepartureFrequency, typically two trains per hour to London Waterloo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDepartureFrequency Context triple: [Alton railway station, hasDepartureFrequency, typically two trains per hour to London Waterloo]
-
A.
transitFrequencyApprox
chosen
Indicates an approximate rate or regularity with which a transit event or service occurs between entities.
-
B.
hasDepartureSide
Indicates the side or direction from which an entity departs or leaves a location.
-
C.
departureTime
Indicates the specific time at which an entity leaves or begins its departure from a location or state.
-
D.
serviceFrequencyType
Indicates how often a service occurs or is scheduled within a given time period.
-
E.
departsFrom
Indicates that an entity (such as a vehicle, person, or process) begins its movement, journey, or operation starting from a specified location or point of origin.
- 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_69b3451886588190a3dd1305ea7c58dc |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b350d8bff88190bcf7dd419d5f4312 |
completed | March 12, 2026, 11:48 p.m. |
| PD | Predicate disambiguation | batch_69b34f4a07b08190a06ada0d9cbb14fb |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:11 p.m.