This paper examines the Stanford typed dependencies (SD) representation, designed to provide a straightforward and semantically contentful description of grammatical relations for users who need to extract textual relations. The authors argue that dependency schemes must be simple and provide useful information for automatic text understanding. They compare the SD scheme to the GR and PARC representations, highlighting its design principles and suitability for parser evaluation. The SD scheme aims to be user-friendly, focusing on binary relations between content words and maintaining semantically useful information while ignoring less relevant linguistic details. It offers two options: one that preserves the original sentence structure and another that collapses certain words to facilitate relation extraction. The paper discusses the design choices, including uniform representation, content word heads, and binary relations, and compares the SD scheme's performance with GR and PARC in practical applications. The Stanford parser tool is also described, which automatically extracts grammatical relations from phrase structure parses. The SD scheme has been successfully used in various domains, including text understanding, bioinformatics, and biomedical applications, and is considered suitable for parser evaluation due to its practicality and effectiveness in task-based tasks.This paper examines the Stanford typed dependencies (SD) representation, designed to provide a straightforward and semantically contentful description of grammatical relations for users who need to extract textual relations. The authors argue that dependency schemes must be simple and provide useful information for automatic text understanding. They compare the SD scheme to the GR and PARC representations, highlighting its design principles and suitability for parser evaluation. The SD scheme aims to be user-friendly, focusing on binary relations between content words and maintaining semantically useful information while ignoring less relevant linguistic details. It offers two options: one that preserves the original sentence structure and another that collapses certain words to facilitate relation extraction. The paper discusses the design choices, including uniform representation, content word heads, and binary relations, and compares the SD scheme's performance with GR and PARC in practical applications. The Stanford parser tool is also described, which automatically extracts grammatical relations from phrase structure parses. The SD scheme has been successfully used in various domains, including text understanding, bioinformatics, and biomedical applications, and is considered suitable for parser evaluation due to its practicality and effectiveness in task-based tasks.