Triple
T2045902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | HBCUs |
E45449
|
entity |
| Predicate | policyRelevance |
P1876
|
FINISHED |
| Object | subject of federal and state support initiatives |
—
|
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: subject of federal and state support initiatives | Statement: [HBCUs, policyRelevance, subject of federal and state support initiatives]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: policyRelevance Context triple: [HBCUs, policyRelevance, subject of federal and state support initiatives]
-
A.
policyImplication
Indicates that one policy, decision, or condition leads to, justifies, or necessitates another policy outcome or course of action.
-
B.
policyFocus
chosen
Indicates that an entity (such as a person, organization, or document) is primarily concerned with, directed toward, or centered on a particular policy area or issue.
-
C.
policyLevel
Indicates the degree or tier of strictness, scope, or priority associated with a given policy.
-
D.
policyStance
Indicates the position or viewpoint an entity holds regarding a specific policy or set of policies.
-
E.
policyContext
Indicates the situational or regulatory framework within which a policy is defined, interpreted, or applied.
- 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_69a8891948208190ab7898da21824c77 |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abbc2c3f6c8190aff07097b2654e52 |
completed | March 7, 2026, 5:48 a.m. |
| PD | Predicate disambiguation | batch_69abb7aa00d4819086d347d9a08f81a0 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:39 p.m.