Triple
T25400856
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wood Street railway station |
E636411
|
entity |
| Predicate | railcodeSystem |
P158825
|
FINISHED |
| Object | National Rail |
—
|
NE NERFINISHED |
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: National Rail | Statement: [Wood Street railway station, railcodeSystem, National Rail]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: railcodeSystem Context triple: [Wood Street railway station, railcodeSystem, National Rail]
-
A.
railcode
Indicates that an entity is associated with a specific railway code used for identification or classification within a rail system.
-
B.
railSystemType
Indicates the specific category or classification of a rail transportation system that an entity belongs to or operates within.
-
C.
railwayLineNumberingSystem
Indicates a system that assigns and manages identifying numbers for railway lines within a rail network.
-
D.
railwayCodeType
Indicates the specific classification or type category assigned to a railway code within a railway coding system.
-
E.
railwaySystemPartOf
Indicates that one railway-related component or subsystem belongs to, is included within, or forms a constituent part of a larger railway system.
- 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_69e75db263888190b77fff9e2827b9a2 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f584f978a881909842e36f61b9a40a |
completed | May 2, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69f4806d93dc8190b9dff4c63186faff |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 1:50 p.m.