Triple
T28692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Community Development Financial Institutions Fund |
E571
|
entity |
| Predicate | programType |
P2192
|
FINISHED |
| Object | financial assistance program |
—
|
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: financial assistance program | Statement: [Community Development Financial Institutions Fund, programType, financial assistance program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programType Context triple: [Community Development Financial Institutions Fund, programType, financial assistance program]
-
A.
program
Indicates that an entity creates, writes, or develops a computer program or software application.
-
B.
programmingLanguage
Indicates that one entity is a programming language used to create, control, or interact with the other entity.
-
C.
standardType
Indicates that one entity is classified as the standard, canonical, or reference type for another entity or context.
-
D.
educationType
Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
-
E.
technologyType
Indicates the specific kind or category of technology associated with an entity or relationship.
- 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_69a2479dec388190967ba648663442c9 |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24925607c8190a9ce7ec834f3e5bb |
completed | Feb. 28, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69a2486bd74c81908d32be3c7d22f51f |
completed | Feb. 28, 2026, 1:44 a.m. |
| PDg | Predicate description generation | batch_69a249246968819099985f13127063d2 |
completed | Feb. 28, 2026, 1:47 a.m. |
Created at: Feb. 28, 2026, 1:44 a.m.