Text Processing Pipeline Workflow
Typical stages in preprocessing text for NLP applications
Before applying sophisticated machine learning models, NLP systems typically perform basic text processing to standardize and clean input data. This flowchart illustrates the typical preprocessing pipeline that ensures consistency and reduces noise in text data.
flowchart TD
Start([Raw Text Input]):::startNode
Step1[Lowercase Conversion]:::processNode
Step2[Special Character Removal]:::processNode
Step3[Whitespace Normalization]:::processNode
Decision1{Keep Punctuation?}:::decisionNode
Step4a[Remove Punctuation]:::processNode
Step4b[Preserve Punctuation]:::processNode
Step5[Tokenization]:::processNode
Decision2{Apply Stemming/Lemmatization?}:::decisionNode
Step6a[Apply Morphological Processing]:::processNode
Step6b[Keep Original Tokens]:::processNode
End([Processed Tokens Ready]):::endNode
Start --> Step1
Step1 --> Step2
Step2 --> Step3
Step3 --> Decision1
Decision1 -->|No| Step4a
Decision1 -->|Yes| Step4b
Step4a --> Step5
Step4b --> Step5
Step5 --> Decision2
Decision2 -->|Yes| Step6a
Decision2 -->|No| Step6b
Step6a --> End
Step6b --> End
classDef startNode fill:#667eea,stroke:#333,stroke-width:2px,color:#fff,font-size:16px
classDef endNode fill:#4facfe,stroke:#333,stroke-width:2px,color:#fff,font-size:16px
classDef processNode fill:#764ba2,stroke:#333,stroke-width:2px,color:#fff,font-size:16px
classDef decisionNode fill:#f093fb,stroke:#333,stroke-width:2px,color:#333,font-size:16px,font-weight:bold
linkStyle default stroke:#999,stroke-width:2px
Note: Each step in this pipeline serves a specific purpose:
- Lowercase Conversion: Treats "Python," "python," and "PYTHON" as identical
- Special Character Removal: Filters out emoji, symbols, excessive punctuation
- Whitespace Normalization: Ensures consistent spacing
- Punctuation Handling: Application-dependent—keep for sentence boundaries, remove for keyword matching
- Tokenization: Splits text into words or subwords for analysis
- Stemming/Lemmatization: Reduces inflected words to their root form
The choice of which steps to apply depends on the downstream NLP task. For example, sentiment analysis might preserve punctuation (exclamation marks indicate emphasis), while keyword search might remove all punctuation for simpler matching.