Concepts
Core concepts that underpin the Computational Linguistics suite.
Pipeline Architecture
The 5-phase model (Scope → Acquire → Analyze → Evaluate → Release), how specialist skills map to each phase, workspace state structure, and the optional Phase 4 Mindset stubs.
Typological Profiling
How URIEL typological distance vectors are used to select transfer sources and predict ML model behavior. Covers key outlier features (polysynthesis, tone, agglutination, root-and-pattern, evidentiality) and the databases used (WALS, Grambank, URIEL, Glottolog).
Joshi Classification
The 6-level resource classification system (Classes 0–5) from Joshi et al. (ACL 2020), with language examples, strategy implications, and the multi-dimensional nature of resource class assessment.
Shared Utilities
The _linguistic_shared/ library — interaction_utils.py and findings_presenter.py — that provide consistent workspace state management and findings presentation across all 18 skills.
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Cross-Suite Integration Guide
Using Data Science and Computational Linguistics together — patterns for combining general data pipelines with language-specific analysis.
Pipeline Architecture
The 5-phase linguistic pipeline model — Scope, Acquire, Analyze, Evaluate, Release — and how specialist skills map to each phase.