Triple
T31227423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heal the World Foundation |
E796179
|
entity |
| Predicate | hasMainBeneficiaries |
P1806
|
FINISHED |
| Object | children |
—
|
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: children | Statement: [Heal the World Foundation, hasMainBeneficiaries, children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainBeneficiaries Context triple: [Heal the World Foundation, hasMainBeneficiaries, children]
-
A.
hasNotableBeneficiary
Indicates that an entity has a significant recipient who benefits from its actions, resources, or outcomes.
-
B.
primaryBeneficiaries
chosen
Indicates which entities are the main recipients or advantaged parties resulting from a particular action, resource, or arrangement.
-
C.
canHaveBeneficiary
Indicates that an entity is capable of having another party designated as its beneficiary, who may receive benefits, rights, or proceeds associated with it.
-
D.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
-
E.
hasEndowmentBeneficiary
Indicates that an entity is designated to receive benefits or distributions from another entity’s endowment.
- 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_69f224da98f88190ab32f690cce5d303 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a0008225cc081909ff1fd0639859dc4 |
completed | May 10, 2026, 4:22 a.m. |
| PD | Predicate disambiguation | batch_6a0007bac5d8819098aff8031d4abe5d |
completed | May 10, 2026, 4:21 a.m. |
Created at: April 29, 2026, 9:10 p.m.