The appearance of new verbs can be observed regularly, but verbs are not frequently investigated in neology, and they are difficult to detect automatically. In this study, a corpus-based method is proposed to detect Spanish verbs with a series of algorithms that analyse the morphology of regular verbs. The vocabulary was drawn from a large corpus and contrasted with a major dictionary of Spanish. Then, a series of filters were applied to distinguish between valid neologism candidates and spelling mistakes. Around 88% of the neologisms proposed by the method were correct and we estimate that the system detected 76% of the neologisms present in the corpus. This procedure can be included in the workflow of a lexicographic project as a regular part of the task, as a systematic way of collecting new verbs from the data and avoiding under-representation or bias.

中文翻译：

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新动词和词典：一种自动检测西班牙语动词中新词的方法

新动词的出现可以经常观察到，但动词在新学中的研究并不频繁，难以自动检测。在这项研究中，提出了一种基于语料库的方法，通过一系列分析规则动词形态的算法来检测西班牙语动词。词汇来自一个大型语料库，并与一本主要的西班牙语词典进行对比。然后，应用一系列过滤器来区分有效的新词候选和拼写错误。该方法提出的新词中约有 88% 是正确的，我们估计该系统检测到语料库中存在的 76% 的新词。此过程可以作为任务的常规部分包含在词典项目的工作流程中，