{"record_id":"grants-2026-001","collected_at":"2026-05-07T09:00:00Z","source_id":"grant_feed","source_url":"https://example.org/grants/ai-learning-analytics","title":"AI learning analytics planning grant","text":"A planning grant invites teams to prototype AI-supported learning analytics dashboards for advising and curriculum improvement.","review_state":"needs_review","nlp":{"summary":"Funding opportunity for AI-supported learning analytics dashboards with advising and curriculum use cases.","topic_labels":["funding","learning analytics","dashboard"],"key_phrases":["planning grant","learning analytics","advising"],"entities":[{"text":"AI","label":"TECHNOLOGY"},{"text":"learning analytics","label":"METHOD"}],"sentiment":"neutral","priority":"high","confidence":0.91,"review_reason":"High relevance to dashboard funding and implementation planning.","model_version":"starter-schema-v1"}}
{"record_id":"papers-2026-014","collected_at":"2026-05-07T09:05:00Z","source_id":"paper_search","source_url":"https://example.org/papers/nlp-feedback-dashboard","title":"NLP dashboards for student feedback triage","text":"The paper describes a pipeline that collects open-ended course feedback, extracts themes, estimates urgency, and routes comments to a review queue.","review_state":"reviewed","nlp":{"summary":"Research paper showing how NLP can turn open-ended course feedback into themes, urgency scores, and a review workflow.","topic_labels":["student feedback","NLP","triage"],"key_phrases":["open-ended feedback","urgency","review queue"],"entities":[{"text":"NLP","label":"METHOD"},{"text":"course feedback","label":"DATA_TYPE"}],"sentiment":"positive","priority":"medium","confidence":0.86,"review_reason":"Useful methodological benchmark, but not an immediate action item.","model_version":"starter-schema-v1"}}
{"record_id":"policy-2026-008","collected_at":"2026-05-07T09:10:00Z","source_id":"policy_monitor","source_url":"https://example.org/policy/data-governance-update","title":"Data governance update for automated text analysis","text":"A new guidance memo asks teams to document source permissions, data retention, model prompts, and human review rules before deploying automated text analysis dashboards.","review_state":"needs_review","nlp":{"summary":"Policy memo requiring documentation of source permissions, retention, prompts, and human review for text-analysis dashboards.","topic_labels":["governance","privacy","human review"],"key_phrases":["source permissions","data retention","human review"],"entities":[{"text":"automated text analysis","label":"SYSTEM"},{"text":"data retention","label":"POLICY"}],"sentiment":"mixed","priority":"high","confidence":0.94,"review_reason":"Directly affects dashboard governance and should be checked before deployment.","model_version":"starter-schema-v1"}}