Triple
T11600185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basildon railway station |
E275106
|
entity |
| Predicate | hasSuburbanServices |
P68952
|
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: [Basildon railway station, hasSuburbanServices, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuburbanServices Context triple: [Basildon railway station, hasSuburbanServices, yes]
-
A.
hasSuburbanService
chosen
Indicates that an entity provides or is connected to a public transportation service specifically serving suburban areas, typically linking suburbs with urban centers.
-
B.
hasSuburbanServiceBrand
Indicates that an entity operates or is associated with a specific brand used for its suburban transport services.
-
C.
hasSuburbanSection
Indicates that a larger route, line, or area includes a portion that passes through or serves a suburban region.
-
D.
isSuburbanHub
Indicates that a location functions as a primary activity or transit center within a suburban area, serving surrounding neighborhoods.
-
E.
hasSuburbanRole
Indicates that one entity holds or performs a role, function, or status specifically associated with a suburban context in relation to another entity.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8954c3c248190bcccd4c7ff667b3a |
completed | April 10, 2026, 6:14 a.m. |
| PD | Predicate disambiguation | batch_69d85dd20d188190863d1190d4c16048 |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.