Triple
T25457945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stadion An der Alten Försterei |
E637963
|
entity |
| Predicate | supporterVolunteerHours |
P145437
|
FINISHED |
| Object | over 140,000 |
—
|
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: over 140,000 | Statement: [Stadion An der Alten Försterei, supporterVolunteerHours, over 140,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supporterVolunteerHours Context triple: [Stadion An der Alten Försterei, supporterVolunteerHours, over 140,000]
-
A.
hasVolunteerCount
chosen
Indicates the number of volunteers associated with a particular entity or activity.
-
B.
volunteeredFor
Indicates that an entity willingly offered their time or services to support or participate in an activity, cause, or organization.
-
C.
usesVolunteers
Indicates that an entity relies on or engages volunteers to perform its activities or services.
-
D.
hasVolunteerParticipation
Indicates that an entity is involved in or benefits from activities performed by volunteers.
-
E.
hasVolunteerStatus
Indicates that an entity holds a particular volunteer-related status or role within a specified context.
- 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_69e75db8bab08190baca80b4a8c315fd |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 21, 2026, 2:10 p.m.