Labelers will create a ground-truth dataset by pairing each anonymized financial document (PDF/XLS/image) with a corrected, structured JSON output. The task consists of : 1) Gather ~10 various financial documents (we will provide support) 2) Extract the required client financial information (primarily assets, liabilities, account/holding details, balances, currencies, dates, and identifying attributes) 3) populate our provided JSON schema/template accurately 4) validate JSON formatting and completeness 5) flag/indicate any ambiguities or missing information using tags/notes. The outcome is a set of document + JSON “correction” pairs used that we will use to benchmark our model performance and detect improvements/regressions over time.
Estimated Total Earnings
$300.00
Fixed Price
$300.00
Time Requirement
Less than 20 hrs/week
Duration
1-3 months
Anonymized financial client documents (PDF/XLS/images)
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Hiring Type
Required Location
Workload / Schedule
First dataset of 10 documents + annotation within the first week, to be continued if satisfied with the outcome
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Data Type
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Subject Matter / Industry
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