Triple
T5794192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Public Law 101-625 |
E128466
|
entity |
| Predicate | providesFundingFor |
P33009
|
FINISHED |
| Object | rental 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: rental assistance | Statement: [Public Law 101-625, providesFundingFor, rental assistance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: providesFundingFor Context triple: [Public Law 101-625, providesFundingFor, rental assistance]
-
A.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
-
B.
funderOf
chosen
Indicates that one entity provides financial support or funding for another entity, project, or activity.
-
C.
fundingComponent
Indicates that one entity serves as a financial contributor or funding source for another entity or activity.
-
D.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
-
E.
funderType
Indicates the category or kind of organization or individual that provides funding in the relationship.
- 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_69c00845ca68819081a2ce3ecca577f7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02b1304588190b59a18fb7b70a60f |
completed | March 22, 2026, 5:46 p.m. |
| PD | Predicate disambiguation | batch_69c021d477008190946113f9859eeb90 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:51 p.m.