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Document AnnotationText AnnotationText Labeling

Document Annotation for Financial Services

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For one of our LegalTech clients, we annotated over 6,000 complex legal documents to extract entities and logical relationships between them. The project required a customized annotation pipeline due to the specific logic of legal texts, where a single word can alter the meaning of an entire clause.

Industry Financial Industry
Data 6,000 documents, 20 task types
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Industry Financial Industry
Data 6,000 documents, 20 task types

Task:

The client requested the annotation of legal documents using Label Studio. The goal was to highlight key legal entities (such as seller, buyer, alienated right, and representative) and accurately establish relationships between them.

Key challenges included:

  • Complex legal language and conditional constructions
  • High sensitivity to errors — missing or misinterpreting even one word could distort the annotation
  • Lack of standardization across documents (contracts, inheritance certificates, etc.)

Solution:

  • 01

    Preparation and workflow organization:

    • Developed detailed technical guidelines tailored to 20+ annotation scenarios
    • Created a document with Q&A updates from the client to clarify edge cases
    • Provided annotated examples with screenshots for each entity type
    • Recorded training videos and provided personalized video feedback on initial tasks
    • Implemented a helpdesk-style internal communication channel for quick resolution of questions
  • 02

    Data annotation:

    • Annotators identified core legal entities and manually mapped relationships (e.g., linking an alienated right to both the seller and the asset)
    • Ensured structural consistency (e.g., linking a representative to the main party in the transaction)
    • Used Label Studio for precise control over annotation fields and linkage logic
  • 03

    Quality control:

    • Each document was reviewed by validators, who provided structured feedback
    • Errors were described in detail in validation spreadsheets and returned for correction
    • Continuous feedback loops improved overall annotation quality over time

Results:

  • Delivered high-precision annotations across 6,000 legal documents

  • Enhanced annotator expertise through ongoing training and review cycles

  • Built a scalable system for handling non-standard annotation logic in legal texts

  • Maintained quality and consistency across a high-complexity dataset

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