Triple
T9675386
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Race for Life fundraising series |
E234132
|
entity |
| Predicate | charitySubsector |
P9241
|
FINISHED |
| Object | cancer charities |
—
|
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: cancer charities | Statement: [Race for Life fundraising series, charitySubsector, cancer charities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: charitySubsector Context triple: [Race for Life fundraising series, charitySubsector, cancer charities]
-
A.
nonProfitSector
Indicates that an entity operates within or is associated with the nonprofit sector, typically focusing on mission-driven rather than profit-driven activities.
-
B.
nonprofitType
Indicates the specific category or classification of a nonprofit organization based on its legal or functional type.
-
C.
fieldOfPhilanthropy
chosen
Indicates that an entity is engaged in or associated with a particular area or domain of philanthropic activity.
-
D.
associatedCharity
Indicates that one entity has a formal or recognized charitable affiliation or partnership with another entity.
-
E.
regionOfPhilanthropy
Indicates the geographic area or location where philanthropic activities, donations, or charitable efforts are directed or take place.
- 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_69ca848f55e48190b3f67252571c3d45 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9c6ed62081908863f2ea0e98961a |
completed | April 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b5d40c8190850ad7a351445f32 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:15 p.m.