Triple
T16228382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cultural Equity Grants program |
E393914
|
entity |
| Predicate | eligibilityArea |
P122239
|
FINISHED |
| Object | San Francisco-based artists |
—
|
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: San Francisco-based artists | Statement: [Cultural Equity Grants program, eligibilityArea, San Francisco-based artists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eligibilityArea Context triple: [Cultural Equity Grants program, eligibilityArea, San Francisco-based artists]
-
A.
eligibility
Indicates that an entity meets the required conditions or qualifications to participate in, receive, or perform something.
-
B.
eligibilityContext
Indicates the situational or conditional factors under which an entity qualifies for or is considered eligible for something.
-
C.
eligibilityLevel
Indicates the degree or tier of qualification an entity has for a given benefit, service, or status.
-
D.
eligibilityCategory
Indicates the classification or type of eligibility that applies to an entity within a given context.
-
E.
eligibilityFocus
Indicates that the relationship or action centers on determining or specifying what qualifies an entity as eligible within a given context.
- 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_69d87f204df88190a8f88923decf9835 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e23d2785f88190ae80d5d61129d3e5 |
completed | April 17, 2026, 2:01 p.m. |
| PD | Predicate disambiguation | batch_69e219e94a448190b73a4e6aa374eb4a |
completed | April 17, 2026, 11:30 a.m. |
| PDg | Predicate description generation | batch_69e21e55a2388190b29a045a8c608ba4 |
completed | April 17, 2026, 11:49 a.m. |
Created at: April 10, 2026, 5:03 a.m.