Triple
T6454988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASCC |
E139969
|
entity |
| Predicate | coversPolicyAreas |
P5037
|
FINISHED |
| Object | education |
—
|
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: education | Statement: [ASCC, coversPolicyAreas, education]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversPolicyAreas Context triple: [ASCC, coversPolicyAreas, education]
-
A.
coversPolicyArea
chosen
Indicates that a policy, document, or initiative includes or addresses a particular policy area or topic within its scope.
-
B.
hasPolicyArea
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
C.
commonPolicyArea
Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
-
D.
supportsPolicyArea
Indicates that one entity endorses, advocates for, or is in favor of a particular policy area or domain of public policy.
-
E.
isPartOfPolicyArea
Indicates that one policy, topic, or issue belongs to, falls under, or is categorized within a broader policy area or domain.
- 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_69c008b301948190a35854e5284dc822 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d339788190992e3299ffe30d58 |
completed | March 22, 2026, 10:14 p.m. |
| PD | Predicate disambiguation | batch_69c0673b44148190aed70084f0ff4992 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:48 p.m.