We introduce the logical grammar emdebbing (LGE), a model inspired by pregroup grammars and categorial grammars to enable unsupervised inference of lexical categories and syntactic rules from a corpus of text. LGE produces comprehensible output summarizing its inferences, has a completely transparent process for producing novel sentences, and can learn from as few as a hundred sentences.

翻译：我们提出了逻辑语法嵌入（LGE），这是一种受预群语法和范畴语法启发的模型，能够从文本语料库中无监督地推断词汇类别和句法规则。LGE生成的输出可清晰总结其推理过程，具有完全透明的机制用于生成新句子，并且仅需学习数百个句子即可实现上述功能。