Triple
T829065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CARE |
E17922
|
entity |
| Predicate | notableProgramType |
P20471
|
FINISHED |
| Object | cash and voucher assistance |
—
|
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: cash and voucher assistance | Statement: [CARE, notableProgramType, cash and voucher assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableProgramType Context triple: [CARE, notableProgramType, cash and voucher assistance]
-
A.
notableSeries
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
-
B.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
-
C.
notableProgramInvolvement
Indicates that an entity has a significant or distinguished role or participation in a particular program.
-
D.
notableOriginalSeries
Indicates that an entity is recognized as a significant or distinguished original series associated with another entity (such as a platform, creator, or franchise).
-
E.
notableMedia
Indicates a relationship where a media work is recognized as significant, prominent, or especially relevant in connection with a given entity.
- F. None of above. chosen
Provenance (4 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_69a4937c9c188190aaa216f6b466f452 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ab9b458881909aa23f0eb7cbc87f |
completed | March 1, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69a4aa79a6488190a634388e071ed9b7 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4893e481908632102d240466dc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.