Triple
T7207730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Skillman Foundation |
E148709
|
entity |
| Predicate | hasPrimaryBeneficiaries |
P1806
|
FINISHED |
| Object | low-income 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: low-income children | Statement: [Skillman Foundation, hasPrimaryBeneficiaries, low-income children]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryBeneficiaries Context triple: [Skillman Foundation, hasPrimaryBeneficiaries, low-income children]
-
A.
primaryBeneficiaries
chosen
Indicates which entities are the main recipients or advantaged parties resulting from a particular action, resource, or arrangement.
-
B.
eligibleBeneficiaries
Indicates that certain parties meet the required conditions to receive benefits or entitlements under a given rule or program.
-
C.
beneficiaries
Indicates that certain entities receive advantages, profits, or positive outcomes from an action, event, or arrangement.
-
D.
estimatedNumberOfBeneficiaries
Indicates the approximate count of individuals or entities expected to receive benefits from something.
-
E.
hasPrimaryOccupants
Indicates that certain entities are the main or principal occupants of another entity (such as a space, structure, or location).
- 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_69c687e8cf188190b5f3ecffd681f04e |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e969c5fc819096bc03bfba12d0cf |
completed | March 27, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.