The paper presents a method for automatically acquiring hyponymy lexical relations from unrestricted text, aiming to avoid pre-encoded knowledge and applicability across various text genres. The authors identify and describe a set of lexico-syntactic patterns that are easily recognizable, frequently occur, and unambiguously indicate hyponymy. These patterns are used to discover and extract hyponymic relationships from text corpora, which can then be used to augment and critique existing thesauruses, such as WordNet. The approach is compared with other methods in lexical information acquisition from text corpora and is shown to be effective in identifying hyponymic relationships, though with some limitations. The paper also discusses the challenges and future directions for improving the method, including handling more complex noun phrases and applying it to different languages.The paper presents a method for automatically acquiring hyponymy lexical relations from unrestricted text, aiming to avoid pre-encoded knowledge and applicability across various text genres. The authors identify and describe a set of lexico-syntactic patterns that are easily recognizable, frequently occur, and unambiguously indicate hyponymy. These patterns are used to discover and extract hyponymic relationships from text corpora, which can then be used to augment and critique existing thesauruses, such as WordNet. The approach is compared with other methods in lexical information acquisition from text corpora and is shown to be effective in identifying hyponymic relationships, though with some limitations. The paper also discusses the challenges and future directions for improving the method, including handling more complex noun phrases and applying it to different languages.