Implement Batched Classification and Progress Logging

[google-labs-jules]

Implemented batched classification and progress logging for the IC/OOC classification stage (Stage 6) to address performance bottlenecks and user feedback gaps.

Key Changes:

1. Batched Classification (BUG-20251107-03):

   • Implemented classify_segments_batched in OllamaClassifier to process segments in chunks (default 10).
   • Created new JSON-array oriented prompts (classifier_batch_prompt_en.txt, _nl.txt).
   • Added robust error handling: if a batch fails (e.g., malformed JSON), it falls back to sequential classification for those segments to ensure data integrity.
   • Configurable via CLASSIFICATION_USE_BATCHING and CLASSIFICATION_BATCH_SIZE.

2. Progress Logging (BUG-20251107-02):

   • Added periodic progress logging (every 20 segments) to StatusTracker and application logs.
   • Includes completion percentage and ETA estimation.

3. Testing:

   • Verified with unit tests covering batched logic, fallback scenarios, and sequential logging.
   • Updated tests/test_classifier.py and removed temporary tests/test_classifier_v2.py.

4. Fixes:

   • Fixed missing imports (re, time) in src/classifier.py.
   • Updated ClassificationResult.to_dict to include missing fields.

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PR created automatically by Jules for task 12799264901023550111 started by @Gambitnl

[google-labs-jules]

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