: Perfective/imperfective aspect (65A), past tense (66A), future tense (67A), and the perfect (68A).
: Definite (37A) and Indefinite (38A) article systems.
The "RoBERTa" designation suggests this data has been pre-processed or formatted for use with the (Robustly Optimized BERT Pretraining Approach) large language model, likely for tasks like cross-lingual transfer or testing a model's metalinguistic knowledge. Included Linguistic Features (Chapters 37–70) WALS roberta sets 37-70.zip
: Gender assignment (32A), coding of nominal plurality (33A), and the number of cases (49A).
: Ordinal (53A) and distributive (54A) numerals, and numeral classifiers (55A). Nominal Syntax (Chapters 58–64) : : Testing if models like RoBERTa or XLM-RoBERTa
: Leveraging the broad cross-linguistic data in WALS to improve how models handle the hundreds of languages that lack large amounts of training text.
: Testing if models like RoBERTa or XLM-RoBERTa have "learned" the typological rules of specific languages during pre-training. coding of nominal plurality (33A)
The features in this range are essential for understanding how different languages handle noun and verb structures. :