EntityIdentification

Identify whether two sets of data are from the same entity. 识别两组数据是否来自同一主体

This is a MCP (Model Context Protocol) server. 这是一个支持MCP协议的服务器。

Data Comparison Tool

This tool provides a comprehensive way to compare two sets of data, evaluating both exact and semantic equality of their values. It leverages text normalization and a language model to determine if the data originates from the same entity.

Features

Text Normalization: Converts text to lowercase, removes punctuation, and normalizes whitespace.
Value Comparison: Compares values directly and semantically (ignoring order for lists).
JSON Traversal: Iterates through each key in the JSON objects and compares corresponding values.
Language Model Integration: Uses a generative language model to assess semantic similarity and provide a final judgment on whether the data comes from the same entity.

Installation

To use this tool, ensure you have the necessary dependencies installed. You can install them using pip:

pip install genai

Usage

Functions

normalize_text(text):
- Normalizes the input text by converting it to lowercase, removing punctuation, and normalizing whitespace.
compare_values(val1, val2):
- Compares two values both exactly and semantically.
- If the values are lists, it ignores the order of elements for semantic comparison.
compare_json(json1, json2):
- Compares two JSON objects key by key.
- Uses compare_values to evaluate each key's values.
- Integrates a language model to assess semantic similarity and provides a final judgment.

Example

import json
import genai
import re

# Define your JSON objects
json1 = {
    "name": "John Doe",
    "address": "123 Main St, Anytown, USA",
    "hobbies": ["reading", "hiking", "coding"]
}

json2 = {
    "name": "john doe",
    "address": "123 Main Street, Anytown, USA",
    "hobbies": ["coding", "hiking", "reading"]
}

# Compare the JSON objects
comparison_results = compare_json(json1, json2)

# Generate final matching result
model1 = genai.GenerativeModel("gemini-2.0-flash-thinking-exp")
result_matching = model1.generate_content("综合这些信息，你认为可以判断两个数据来自同一主体吗？"+json.dumps(comparison_results, ensure_ascii=False, indent=4))
print(result_matching.text)

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

If you have any questions or suggestions, please contact me:

Email: u3588064@connect.hku.hk
GitHub: u3588064@connect.hku.hk。

Wechat qrcode_for_gh_643efb7db5bc_344(1)

Features

Text Normalization: Converts text to lowercase, removes punctuation, and normalizes whitespace.

Value Comparison: Compares values directly and semantically (ignoring order for lists).

JSON Traversal: Iterates through each key in the JSON objects and compares corresponding values.

Language Model Integration: Uses a generative language model to assess semantic similarity and provide a final judgment on whether the data comes from the same entity.

Usage

Functions

normalize_text(text):

Normalizes the input text by converting it to lowercase, removing punctuation, and normalizing whitespace.

compare_values(val1, val2):

Compares two values both exactly and semantically.
If the values are lists, it ignores the order of elements for semantic comparison.

compare_json(json1, json2):

Compares two JSON objects key by key.
Uses compare_values to evaluate each key's values.
Integrates a language model to assess semantic similarity and provides a final judgment.

Example

import json import genai import re # Define your JSON objects json1 = { "name": "John Doe", "address": "123 Main St, Anytown, USA", "hobbies": ["reading", "hiking", "coding"] } json2 = { "name": "john doe", "address": "123 Main Street, Anytown, USA", "hobbies": ["coding", "hiking", "reading"] } # Compare the JSON objects comparison_results = compare_json(json1, json2) # Generate final matching result model1 = genai.GenerativeModel("gemini-2.0-flash-thinking-exp") result_matching = model1.generate_content("综合这些信息，你认为可以判断两个数据来自同一主体吗？"+json.dumps(comparison_results, ensure_ascii=False, indent=4)) print(result_matching.text)