Triple
T23383371
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buxted railway station |
E593809
|
entity |
| Predicate | isSingleTrackSection |
P107293
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Buxted railway station, isSingleTrackSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSingleTrackSection Context triple: [Buxted railway station, isSingleTrackSection, yes]
-
A.
hasSingleTrackSections
chosen
Indicates that a route or railway line includes sections where only a single track is available for traffic.
-
B.
hasTrackSection
Indicates that an entity includes, is composed of, or is associated with a specific section or segment of a track.
-
C.
nonSingleTrack
Indicates that the subject is associated with more than one track or path, rather than being limited to a single track.
-
D.
isSingle
Indicates that an entity is not currently in a romantic relationship or legally married.
-
E.
isMultiSectional
Indicates that something is composed of or divided into multiple distinct sections or parts.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a496ae34819090e86c89eef6d2dc |
completed | April 29, 2026, 6:26 a.m. |
| PD | Predicate disambiguation | batch_69f061dde2e481908308952f9c0d3c2e |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:34 p.m.