Triple
T23014026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crowhurst railway station |
E572980
|
entity |
| Predicate | hasUnstaffedPeriods |
P150679
|
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: [Crowhurst railway station, hasUnstaffedPeriods, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnstaffedPeriods Context triple: [Crowhurst railway station, hasUnstaffedPeriods, yes]
-
A.
hasWorkPeriod
Indicates that an entity is associated with a specific span of time during which it performs or is engaged in some work or activity.
-
B.
hasStaffedHours
Indicates that specific hours or time periods are assigned during which staff are present and available.
-
C.
hasWorkPeriodStart
Indicates the point in time when a specified work period begins.
-
D.
hasUnstaffedTicketOffice
Indicates that a location or facility has a ticket office present, but it is not staffed by personnel.
-
E.
hasCountingPeriod
Indicates that there is a defined time span or interval over which occurrences, quantities, or measurements related to an entity are counted or aggregated.
- F. None of above. chosen
Provenance (4 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_69e245b764cc8190a51be76f1d9611e1 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f183e3c0e08190a7ac747b056ec3ca |
completed | April 29, 2026, 4:06 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9cd5488190bcd23183179f48cd |
completed | April 27, 2026, 10:34 a.m. |
| PDg | Predicate description generation | batch_69ef538b29c081908fa56ee35a1dcee7 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:51 p.m.