ieg-dhr/NLP-Course4Humanities_2024

The NLP-Course4Humanities_2024 repository is fundamentally an educational resource rather than a software product or infrastructure tool. With only 19 stars and 6 forks after 550+ days, it has very limited traction outside its original classroom context. From a competitive intelligence perspective, it offers no technical moat; the methods described (TF-IDF, POS tagging, NER) are standard industry patterns applied to a specific domain (historical newspapers). While the domain expertise required to curate humanities-specific datasets is non-trivial, the 'code' is easily reproducible by any developer familiar with the Hugging Face or spaCy ecosystems. Frontier labs pose a 'low' risk only because the specific niche of historical newspaper analysis is too small for them to target directly, though general-purpose LLMs (GPT-4, Claude 3) already perform the core tasks described in this course (OCR correction, NER, classification) significantly better than the methods likely taught in a 2024-dated curriculum. Its displacement horizon is short (6 months) because educational content in AI becomes obsolete quickly as new models and simpler libraries emerge.