This paper analyzes multiple deep-syntactic frameworks with the goal of
creating a proposal for a set of universal semantic role labels. The proposal
examines various theoretic linguistic perspectives and focuses on Meaning-Text
Theory and Functional Generative Description frameworks.
For the purpose of this research, data from four languages is used -- Spanish
and Catalan (Taule et al., 2011), Czech (Hajic et al., 2017), and English
(Hajic et al., 2012). This proposal is oriented towards Universal Dependencies
(de Marneffe et al., 2021) with a further intention of applying the universal
semantic role labels to the UD data.

本文旨在通过对多种深层句法框架的分析，提出一组通用的语义角色标签建议，并将其应用于语言数据。建议基于多种理论语言观点，主要聚焦于 Meaning-Text Theory 和 Functional Generative Description 框架。数据来自西班牙语、加泰罗尼亚语、捷克语和英语。建议旨在面向 Universal Dependencies，并将通用语义角色标签用于 UD 数据。

深度句法关系的统一分类

A Unified Taxonomy of Deep Syntactic Relations

The central role of the lexicon in Meaning-Text Theory (MTT) and other
dependency-based linguistic theories cannot be replicated in linguistic
theories based on context-free grammars (CFGs). We describe Tree Adjoining
Grammar (TAG) as a system that arises naturally in the process of lexicalizing
CFGs. A TAG grammar can therefore be compared directly to an Meaning-Text Model
(MTM). We illustrate this point by discussing the computational complexity of
certain non-projective constructions, and suggest a way of incorporating
locality of word-order definitions into the Surface-Syntactic Component of MTT.

本文探讨了词汇在 MTT 和其他依赖型语言理论中的中心作用，并研究了基于上下文无关文法（CFGs）的语言理论中无法复制词汇作用的问题。我们介绍了树邻接语法（TAG）作为一个在词汇化 CFGs 过程中自然产生的系统，并将 TAG 语法与 MTM 直接进行比较，并通过讨论某些非投影结构的计算复杂性，提出了将词序的局部性定义纳入 MTT 的表层句法组成部分的方法。