Triple
T32441398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pageant of the Masters |
E829022
|
entity |
| Predicate | hasVolunteerPerformers |
P118627
|
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: [Pageant of the Masters, hasVolunteerPerformers, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolunteerPerformers Context triple: [Pageant of the Masters, hasVolunteerPerformers, yes]
-
A.
hasAdultVolunteers
Indicates that an entity is associated with one or more adult individuals who volunteer their time or services for it.
-
B.
hasVolunteerPersonnelFrom
Indicates that an entity receives or utilizes volunteer personnel supplied by another entity or source.
-
C.
eligiblePerformers
Indicates that certain entities are qualified or permitted to perform in a specified event, role, or context.
-
D.
hasVolunteerCount
Indicates the number of volunteers associated with a particular entity or activity.
-
E.
hasVolunteerParticipation
chosen
Indicates that an entity is involved in or benefits from activities performed by volunteers.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f739a638748190808e7a2930dce16e |
completed | May 3, 2026, 12:03 p.m. |
| PD | Predicate disambiguation | batch_69f732f2dc6c8190a4e86da98cc5eb05 |
completed | May 3, 2026, 11:35 a.m. |
Created at: May 1, 2026, 12:55 a.m.