Triple
T15395598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trolley Museum of New York |
E368168
|
entity |
| Predicate | hasVolunteerParticipation |
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: [Trolley Museum of New York, hasVolunteerParticipation, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVolunteerParticipation Context triple: [Trolley Museum of New York, hasVolunteerParticipation, yes]
-
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
Indicates that an organization or entity offers an organized program through which individuals can volunteer their time or services.
-
D.
hasAdultVolunteers
Indicates that an entity is associated with one or more adult individuals who volunteer their time or services for it.
-
E.
hasVolunteerBase
Indicates that an entity maintains or relies on a group of volunteers as a foundational support resource.
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ac79081908ac79c0b3e7587ff |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:19 a.m.