# INTENTS It’s a **base**, a dedicated resource of knowledge about a given brand or service. It’s usually customized for a given company. Covers dedicated content in the form. Intents work with [Dictionaries ](/chatbot/4-step-approach-to-chatbot-training-development-of-content-and-interaction/step-4-training-ai-chatbot-understanding-capabilities-based-on-nlu-nlp/intents.md#dictionaries-are-a-specific-type-of-knowledge-base-they-are-vastly-contributing-to-intent-recognition-process-they-may-cover)and [Language corpuses.](/chatbot/4-step-approach-to-chatbot-training-development-of-content-and-interaction/step-4-training-ai-chatbot-understanding-capabilities-based-on-nlu-nlp/intents.md#language-corpus-is-a-large-and-structured-set-of-text-words) Dictionaries are resources of content that enables better query recognition, including synonyms, prefixes and corrections. #### Dictionaries are a specific type of knowledge base. They are vastly contributing to intent recognition process. They may cover: * Generic (Global) synonyms, * Company’s (Brand’s) synonyms, * Prefixes (Intents), * Correction, * Language corpus. Elements located in Dictionaries have high importance: they are searched in parallel with the Main Base or Small Talk Base when user inputs the utterance. #### Language corpus is a large and structured set of text, words. They are used to doing statistical analysis and hypothesis testing, checking occurrences or validating linguistic rules within a specific language territory. The AI-Engineer tool uses language corpuses in natural language processing algorithms. Unlike synonym dictionaries and prefixes, they come pre-set, without the ability of content edit from the level of the Builder tool. Key elements of INTENTS are: * [**Main Intents**](/chatbot/4-step-approach-to-chatbot-training-development-of-content-and-interaction/step-4-training-ai-chatbot-understanding-capabilities-based-on-nlu-nlp/intents/main-intents.md) * [**Labels | Tags**](/chatbot/4-step-approach-to-chatbot-training-development-of-content-and-interaction/step-4-training-ai-chatbot-understanding-capabilities-based-on-nlu-nlp/intents/the-structure-of-intents-labels-or-tags.md) * [**Spiders**](/chatbot/4-step-approach-to-chatbot-training-development-of-content-and-interaction/step-4-training-ai-chatbot-understanding-capabilities-based-on-nlu-nlp/intents/groups-of-question-response-matching-spiders.md) --- # 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://help.inteliwise.com/chatbot/4-step-approach-to-chatbot-training-development-of-content-and-interaction/step-4-training-ai-chatbot-understanding-capabilities-based-on-nlu-nlp/intents.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.