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 https://github.com/Eduard6421/RONLI.

翻译：自然语言推理（NLI）是识别句子对蕴含关系的任务，作为自然语言理解的重要代理指标，目前已成为活跃的研究课题。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，目前尚未有公开可用的罗马尼亚语NLI语料库。为此，我们构建了首个罗马尼亚语自然语言推理语料库（RoNLI），其中包含通过远程监督获得的58K训练句子对，以及经过人工标注正确标签的6K验证集和测试集句子对。我们基于远程学习开展了多项机器学习方法的实验，涵盖从词嵌入浅层模型到基于Transformer的神经网络，以建立具有竞争力的基线系统。此外，我们采用基于数据图谱的新型课程学习策略，进一步优化了最优模型。我们的数据集及复现基线的代码已公开于https://github.com/Eduard6421/RONLI。