Triple
T8945087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burnley Central railway station |
E213200
|
entity |
| Predicate | ticketOfficeHours |
P10068
|
FINISHED |
| Object | part-time staffed |
—
|
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: part-time staffed | Statement: [Burnley Central railway station, ticketOfficeHours, part-time staffed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ticketOfficeHours Context triple: [Burnley Central railway station, ticketOfficeHours, part-time staffed]
-
A.
bookingWindow
Indicates the time period before an event or service during which a booking or reservation can be made.
-
B.
hoursOfOperation
chosen
Indicates the time periods during which a place or service is open and available for use.
-
C.
openingTime
Indicates the time at which a place, service, or event begins operating or becomes accessible.
-
D.
openingHoursCharacteristic
Indicates a relationship that specifies particular attributes or features of an entity’s opening hours, such as patterns, exceptions, or special conditions.
-
E.
ticketDemand
Indicates that there is a level of desire or need among potential buyers for tickets to an event, service, or offering.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc66db998c8190999a7a686bbdda1f |
completed | April 1, 2026, 12:29 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed5267c8190a43feb2a2f3df1ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:59 p.m.