Analyze NLP Methods for Extracting Data from ORCA Log Files as Alternative to Rule-Based Parsing

[SiriChandanaGarimella]

Is your feature request related to a problem? Please describe.
Currently, extracting data from ORCA computational chemistry log files is based on rule-based pattern matching, which has several limitations, like constant maintenance of rules, limited flexibility for different ORCA versions, etc.

Describe the solution you'd like
Need to analyze various NLP approaches that could provide more robust and flexible data extraction:

1. Text Chunking/Segmentation Methods
   • Evaluate algorithms for identifying section boundaries
   • Compare with the current rule-based approach
2. Section Classification Methods
   • TF-IDF vs Word Embeddings
   • BERT vs simpler approaches
3. Data Structure Recognition
   • Methods for table/coordinate data extraction
   • Accuracy requirements

Acceptance Criteria

1. Analysis document comparing different NLP methods
2. Recommendations for best approach
3. Implementation considerations

[SiriChandanaGarimella]

nlp-analysis.pdf

@kungfuchicken - Attached is my NLP analysis documentation. Please check and let me know if any changes are needed.