docs: Update README.md (#7213)

Author: imjoseangel

README.md

@@ -40,7 +40,7 @@ Phoenix is an open-source AI observability platform designed for experimentation
 - [**_Datasets_**](https://docs.arize.com/phoenix/datasets-and-experiments/overview-datasets) - Create versioned datasets of examples for experimentation, evaluation, and fine-tuning.
 - [**_Experiments_**](https://docs.arize.com/phoenix/datasets-and-experiments/overview-datasets#experiments) - Track and evaluate changes to prompts, LLMs, and retrieval.
 - [**_Playground_**](https://docs.arize.com/phoenix/prompt-engineering/overview-prompts)- Optimize prompts, compare models, adjust parameters, and replay traced LLM calls.
-- [**_Prompt Mangement_**](https://docs.arize.com/phoenix/prompt-engineering/overview-prompts/prompt-management)- Manage and test prompt changes systematically using version control, tagging, and experimentation.
+- [**_Prompt Management_**](https://docs.arize.com/phoenix/prompt-engineering/overview-prompts/prompt-management)- Manage and test prompt changes systematically using version control, tagging, and experimentation.
 
 Phoenix is vendor and language agnostic with out-of-the-box support for popular frameworks (🦙[LlamaIndex](https://docs.arize.com/phoenix/tracing/integrations-tracing/llamaindex), 🦜⛓[LangChain](https://docs.arize.com/phoenix/tracing/integrations-tracing/langchain), [Haystack](https://docs.arize.com/phoenix/tracing/integrations-tracing/haystack), 🧩[DSPy](https://docs.arize.com/phoenix/tracing/integrations-tracing/dspy), 🤗[smolagents](https://docs.arize.com/phoenix/tracing/integrations-tracing/hfsmolagents)) and LLM providers ([OpenAI](https://docs.arize.com/phoenix/tracing/integrations-tracing/openai), [Bedrock](https://docs.arize.com/phoenix/tracing/integrations-tracing/bedrock), [MistralAI](https://docs.arize.com/phoenix/tracing/integrations-tracing/mistralai), [VertexAI](https://docs.arize.com/phoenix/tracing/integrations-tracing/vertexai), [LiteLLM](https://docs.arize.com/phoenix/tracing/integrations-tracing/litellm), and more). For details on auto-instrumentation, check out the [OpenInference](https://github.com/Arize-ai/openinference) project.