Triple
T10912252
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Llangollen Railway |
E257728
|
entity |
| Predicate | hasVolunteerInvolvement |
P11190
|
FINISHED |
| Object | volunteer-operated services |
—
|
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: volunteer-operated services | Statement: [Llangollen Railway, hasVolunteerInvolvement, volunteer-operated services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolunteerInvolvement Context triple: [Llangollen Railway, hasVolunteerInvolvement, volunteer-operated services]
-
A.
volunteeredFor
Indicates that an entity willingly offered their time or services to support or participate in an activity, cause, or organization.
-
B.
hasVolunteerStatus
Indicates that an entity holds a particular volunteer-related status or role within a specified context.
-
C.
hasVolunteerProgram
chosen
Indicates that an organization or entity offers an organized program through which individuals can volunteer their time or services.
-
D.
hasAlumniInvolvement
Indicates that an entity maintains an ongoing relationship or engagement with its former members or graduates.
-
E.
hasStudentInvolvement
Indicates that there is participation, engagement, or involvement of one or more students in the referenced activity, event, or 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770723df08190bedfdc94d998f969 |
completed | April 9, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69d70d3f9dc88190a686a8b0dd6a3b21 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:22 p.m.