Triple
T2960936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hough Green railway station |
E80044
|
entity |
| Predicate | hasStaffedHours |
P45233
|
FINISHED |
| Object | limited |
—
|
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: limited | Statement: [Hough Green railway station, hasStaffedHours, limited]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStaffedHours Context triple: [Hough Green railway station, hasStaffedHours, limited]
-
A.
hasWorkSchedule
Indicates that an entity is assigned or follows a specific work schedule, defining when they are expected to work.
-
B.
hasNumberOfShifts
Indicates the quantity of work shifts associated with a given entity.
-
C.
hasStaffedTicketOffice
Indicates that a location or facility has a ticket office that is staffed by personnel.
-
D.
hasAllocatedTime
Indicates that a specific amount or period of time has been reserved or assigned for a particular entity, task, or activity.
-
E.
hasWorkedFor
Indicates that an entity has been employed by or has provided work or services to another entity.
- 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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad995454448190834aa5d47a4ed5ac |
completed | March 8, 2026, 3:44 p.m. |
| PD | Predicate disambiguation | batch_69ad960c5c8881909d679912bd7d78f3 |
completed | March 8, 2026, 3:30 p.m. |
| PDg | Predicate description generation | batch_69ad98379fac8190a4dfe530787703c9 |
completed | March 8, 2026, 3:39 p.m. |
Created at: March 8, 2026, 2:57 p.m.