Triple
T27638499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alcor Life Extension Foundation |
E696526
|
entity |
| Predicate | acceptsFundingFrom |
P163312
|
FINISHED |
| Object | bequests |
—
|
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: bequests | Statement: [Alcor Life Extension Foundation, acceptsFundingFrom, bequests]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: acceptsFundingFrom Context triple: [Alcor Life Extension Foundation, acceptsFundingFrom, bequests]
-
A.
acceptsFundingFrom
chosen
Indicates that one entity receives financial support or funding from another entity.
-
B.
authorizesFundingFor
Indicates that one entity grants official approval or permission for financial resources to be provided to another entity or purpose.
-
C.
permittedFundingFrom
Indicates that providing financial resources from one entity to another is allowed under specified rules or conditions.
-
D.
includesFundingFor
Indicates that one entity’s financial resources or budget allocation explicitly cover or provide funding for another entity, project, or activity.
-
E.
supportsFiatOnRamp
Indicates that an entity provides or enables a way to convert traditional (fiat) currency into digital assets within its system or platform.
- 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_69ef5909f3848190805f35b76833e722 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f63894e5848190aec428392562ab06 |
completed | May 2, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69f6370c8c7c8190a02ea82847bb6e76 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 2:25 p.m.