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In natural language processing (NLP), lexical function is a concept tounambiguously represent semantic and syntactic features of words and phrases intext first crafted in the Meaning-Text Theory. Hierarchical classification oflexical functions involves organizing these features into a tree-like hierarchyof categories or labels. This is a challenging task as it requires a goodunderstanding of the context and the relationships among words and phrases intext. It also needs large amounts of labeled data to train language modelseffectively. In this paper, we present a dataset of most frequent Spanishverb-noun collocations and sentences where they occur, each collocation isassigned to one of 37 lexical functions defined as classes for a hierarchicalclassification task. Each class represents a relation between the noun and theverb in a collocation involving their semantic and syntactic features. Wecombine the classes in a tree-based structure, and introduce classificationobjectives for each level of the structure. The dataset was created bydependency tree parsing and matching of the phrases in Spanish news. We providebaselines and data splits for each objective.

SpaDeLeF: A Dataset for Hierarchical Classification of Lexical Functions for Collocations in Spanish