Triple
T109595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Rail |
E2215
|
entity |
| Predicate | NationalRailEnquiriesPhoneNumber |
P5882
|
FINISHED |
| Object | 03457 48 49 50 |
—
|
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: 03457 48 49 50 | Statement: [National Rail, NationalRailEnquiriesPhoneNumber, 03457 48 49 50]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NationalRailEnquiriesPhoneNumber Context triple: [National Rail, NationalRailEnquiriesPhoneNumber, 03457 48 49 50]
-
A.
hasRailStation
Indicates that one entity possesses, contains, or is served by a rail station.
-
B.
hasRailwayStation
Indicates that a place or location is served by, or contains, a railway station.
-
C.
railwayLine
Indicates that there is a railway line connection or route associated with or passing through the referenced entity.
-
D.
nearestPassengerRailStation
Indicates that one entity is the closest passenger rail station in distance to another entity.
-
E.
trains
Indicates that one entity teaches, instructs, or coaches another entity to develop skills, knowledge, or abilities.
- F. None of above. chosen
Provenance (4 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563fd2fc819090265edbfe3092d6 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a2570f45bc81909ebba7ee5f602976 |
completed | Feb. 28, 2026, 2:46 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.