Request Classification Accuracy
Evaluate the system's accuracy in classifying FOIA requests, efficiency in processing, and effectiveness in detecting and filtering 'robo-requests'.
Evaluation overview
How the linked challenge is judged: tasks, benchmarks, and criteria count.
Task templates
Inputs and expected outputs.
Request Classification Accuracy
Classifies a batch of FOIA requests into predefined categories (e.g., Legitimate, Spam, Ambiguous).
Array of JSON objects, each with 'request_id' (string) and 'content' (string) fields.
JSON object where keys are 'request_id's and values are predicted classification categories (string).
Key Information Extraction
Extracts specific entities (requesting party, subject matter, date range) from legitimate FOIA requests.
JSON object with 'request_id' (string) and 'content' (string) for a legitimate request.
JSON object with extracted fields: 'requesting_party' (string), 'subject_matter' (string), 'date_range' (string).