# Uncommon Types Free text data that is not necessarily common across verticals. Examples: company/business name, product descriptions, reviews, notes, etc. Telmai can offer: Frequency analyzer to identify placeholder or over-represented data Statistical analysis of built-in features (length, spaces, tokens etc) Language detection (separate data from different geographies) \[for distant future] Tokenization and NLP analysis of frequent or important words ML score (our DQ score) --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.telm.ai/academy/correctness/uncommon-types.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.