We present a new corpus of Twitter data annotated for codeswitching and
borrowing between Spanish and English. The corpus contains 9,500 tweets
annotated at the token level with codeswitches, borrowings, and named entities.
This corpus differs from prior corpora of codeswitching in that we attempt to
clearly define and annotate the boundary between codeswitching and borrowing
and do not treat common "internet-speak" ('lol', etc.) as codeswitching when
used in an otherwise monolingual context. The result is a corpus that enables
the study and modeling of Spanish-English borrowing and codeswitching on
Twitter in one dataset. We present baseline scores for modeling the labels of
this corpus using Transformer-based language models. The annotation itself is
released with a CC BY 4.0 license, while the text it applies to is distributed
in compliance with the Twitter terms of service.

本文介绍了一个新的 Twitter 数据语料库，其中包含被注释为西班牙语和英语之间的代码切换或借用的 9,500 个推文，旨在清晰定义代码切换和借入之间的界限，并可用于研究和建模 Twitter 上的西班牙语 - 英语借用和代码切换，最终给出了基于 Transformer 模型的语言模型的基准得分。