In natural language processing (NLP), lexical function is a concept to
unambiguously represent semantic and syntactic features of words and phrases in
text first crafted in the Meaning-Text Theory. Hierarchical classification of
lexical functions involves organizing these features into a tree-like hierarchy
of categories or labels. This is a challenging task as it requires a good
understanding of the context and the relationships among words and phrases in
text. It also needs large amounts of labeled data to train language models
effectively. In this paper, we present a dataset of most frequent Spanish
verb-noun collocations and sentences where they occur, each collocation is
assigned to one of 37 lexical functions defined as classes for a hierarchical
classification task. Each class represents a relation between the noun and the
verb in a collocation involving their semantic and syntactic features. We
combine the classes in a tree-based structure, and introduce classification
objectives for each level of the structure. The dataset was created by
dependency tree parsing and matching of the phrases in Spanish news. We provide
baselines and data splits for each objective.

在本文中，我们介绍了一个包含西班牙语最常见动宾短语及其出现句子的数据集，每个动宾短语都被分配到 37 个词汇功能中的一个类别，用于执行一个分层分类任务。我们将这些类别组合成一个基于树结构的体系，并为每个层级引入了分类目标。该数据集通过对西班牙新闻中的短语进行依赖树解析和匹配而创建，我们提供了每个目标的基准和数据拆分。

SpaDeLeF：西班牙语词搭结构的层次分类数据集

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

We consider the semantics of prepositions, revisiting a broad-coverage
annotation scheme used for annotating all 4,250 preposition tokens in a 55,000
word corpus of English. Attempts to apply the scheme to adpositions and case
markers in other languages, as well as some problematic cases in English, have
led us to reconsider the assumption that a preposition's lexical contribution
is equivalent to the role/relation that it mediates. Our proposal is to embrace
the potential for construal in adposition use, expressing such phenomena
directly at the token level to manage complexity and avoid sense proliferation.
We suggest a framework to represent both the scene role and the adposition's
lexical function so they can be annotated at scale---supporting automatic,
statistical processing of domain-general language---and sketch how this
representation would inform a constructional analysis.

该论文重新考虑了一个广泛覆盖的注释方案，认为介词的词汇贡献不等同于介词所介导的角色 / 关系，并提出了一个用于表示场景角色和介词词汇功能的框架，从而实现了构建分析。