Triple
T22672151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Creswell railway station |
E560244
|
entity |
| Predicate | hasUnstaffedStatus |
P75022
|
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: [Creswell railway station, hasUnstaffedStatus, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnstaffedStatus Context triple: [Creswell railway station, hasUnstaffedStatus, yes]
-
A.
hasWorkStatus
Indicates the current employment or occupational state associated with an entity, such as whether it is active, inactive, or in a specific work condition.
-
B.
hasUnstaffedTicketOffice
chosen
Indicates that a location or facility has a ticket office present, but it is not staffed by personnel.
-
C.
hasStaffedHours
Indicates that specific hours or time periods are assigned during which staff are present and available.
-
D.
hasDutyStatus
Indicates that an entity currently holds a particular duty or operational status in relation to a role, task, or assignment.
-
E.
hasUnitStatus
Indicates that an entity is associated with a particular operational or condition status as a unit.
- 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_69e2454bfd00819099115715a22cb057 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17820a8088190bc0ce907adf95863 |
completed | April 29, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69ee62a6245881909506ff502da14137 |
completed | April 26, 2026, 7:08 p.m. |
Created at: April 17, 2026, 3:10 p.m.