Triple
T5836578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Walton-on-Thames railway station |
E129484
|
entity |
| Predicate | hasSuburbanCommuterRole |
P56763
|
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: [Walton-on-Thames railway station, hasSuburbanCommuterRole, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuburbanCommuterRole Context triple: [Walton-on-Thames railway station, hasSuburbanCommuterRole, yes]
-
A.
hasSuburbanRole
chosen
Indicates that one entity holds or performs a role, function, or status specifically associated with a suburban context in relation to another entity.
-
B.
hasUrbanRole
Indicates that an entity plays a specific functional or social role within an urban or city context.
-
C.
isSuburbanCommunity
Indicates that a community is located in a suburban area, typically characterized by residential neighborhoods situated between urban centers and rural regions.
-
D.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
-
E.
isSuburbanCommunityIn
Indicates that a suburban community is located within or belongs to a specified larger geographic or administrative area.
- 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_69c0084af79c81908af128ccc29983d0 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03341e5888190a5f219b6f92cb161 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:54 p.m.