Triple
T13149543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St Thomas (Exeter) railway station |
E312426
|
entity |
| Predicate | isSuburbanStop |
P49504
|
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: [St Thomas (Exeter) railway station, isSuburbanStop, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSuburbanStop Context triple: [St Thomas (Exeter) railway station, isSuburbanStop, yes]
-
A.
isSuburbanStationOf
Indicates that a station is located in a suburban area and functionally serves as a subsidiary or outlying station of a main or central station.
-
B.
isSuburbanHub
Indicates that a location functions as a primary activity or transit center within a suburban area, serving surrounding neighborhoods.
-
C.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
-
D.
isRuralStop
Indicates that a stop is located in a rural or sparsely populated area rather than in an urban or suburban setting.
-
E.
isInSuburbanArea
chosen
Indicates that something is located within a suburban area, typically between urban and rural regions.
- 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_69d806aabde48190899e13e41659cae5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:11 p.m.