Natural language inference (NLI), the task of recognizing the entailment relationship in sentence pairs, is an actively studied topic serving as a proxy for natural language understanding. Despite the relevance of the task in building conversational agents and improving text classification, machine translation and other NLP tasks, to the best of our knowledge, there is no publicly available NLI corpus for the Romanian language. To this end, we introduce the first Romanian NLI corpus (RoNLI) comprising 58K training sentence pairs, which are obtained via distant supervision, and 6K validation and test sentence pairs, which are manually annotated with the correct labels. We conduct experiments with multiple machine learning methods based on distant learning, ranging from shallow models based on word embeddings to transformer-based neural networks, to establish a set of competitive baselines. Furthermore, we improve on the best model by employing a new curriculum learning strategy based on data cartography. Our dataset and code to reproduce the baselines are available at https://github.com/Eduard6421/RONLI.

翻译：自然语言推理（NLI）是识别句子对中蕴含关系的任务，作为自然语言理解的代理任务受到广泛研究。尽管该任务在构建对话系统、改进文本分类、机器翻译及其他自然语言处理任务中具有重要价值，但据我们所知，目前尚无公开可用的罗马尼亚语NLI语料库。为此，我们发布了首个罗马尼亚语NLI语料库（RoNLI），包含通过远程监督获取的58K训练句子对，以及经过人工标注正确标签的6K验证和测试句子对。我们采用多种基于远程学习的机器学习方法进行实验（从基于词嵌入的浅层模型到基于Transformer的神经网络），建立了一系列具有竞争力的基线模型。此外，我们通过基于数据图谱的新型课程学习策略改进了最优模型。数据集和可复现基线模型的代码发布在https://github.com/Eduard6421/RONLI。