EntityIdentification
by u3588064
This tool compares two sets of data to determine if they originate from the same entity by evaluating both exact and semantic equality. It leverages text normalization and a language model for comprehensive comparison.
Last updated: N/A
What is EntityIdentification?
EntityIdentification is a tool for comparing two sets of data, evaluating both exact and semantic equality of their values to determine if the data originates from the same entity. It is also a MCP (Model Context Protocol) server.
How to use EntityIdentification?
To use this tool, install the required dependencies using pip install genai. Then, define your JSON objects and use the compare_json function to compare them. The function utilizes text normalization, value comparison, and a language model to provide a final judgment on whether the data comes from the same entity.
Key features of EntityIdentification
Text Normalization
Value Comparison
JSON Traversal
Language Model Integration
Use cases of EntityIdentification
Identifying duplicate customer records
Matching product listings from different sources
Verifying user identity across platforms
Detecting fraudulent activities based on data patterns
FAQ from EntityIdentification
What is text normalization?
What is text normalization?
Text normalization converts text to lowercase, removes punctuation, and normalizes whitespace.
How does value comparison work?
How does value comparison work?
Value comparison compares values directly and semantically, ignoring order for lists.
What is JSON Traversal?
What is JSON Traversal?
JSON traversal iterates through each key in the JSON objects and compares corresponding values.
How does the language model assess semantic similarity?
How does the language model assess semantic similarity?
The language model uses a generative approach to assess semantic similarity and provides a final judgment on whether the data comes from the same entity.
What dependencies are required?
What dependencies are required?
The primary dependency is genai, which can be installed using pip.