graphrag/entity_resolution_prompt.py

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ENTITY_RESOLUTION_PROMPT = """
-Goal-
Please answer the following Question as required

-Steps-
1. Identify each line of questioning as required

2. Return output in English as a single list of each line answer in steps 1. Use **{record_delimiter}** as the list delimiter.

######################
-Examples-
######################
Example 1:

Question:
When determining whether two Products are the same, you should only focus on critical properties and overlook noisy factors. 

Demonstration 1: name of Product A is : "computer", name of Product B is :"phone"  No, Product A and Product B are different products.
Question 1: name of Product A is : "television", name of Product B is :"TV"  
Question 2: name of Product A is : "cup", name of Product B is :"mug"  
Question 3: name of Product A is : "soccer", name of Product B is :"football"  
Question 4: name of Product A is : "pen", name of Product B is  :"eraser"  

Use domain knowledge of Products to help understand the text and answer the above 4 questions in the format: For Question i, Yes, Product A and Product B are the same product. or  No, Product A and Product B are different products. For Question i+1, (repeat the above procedures)
################
Output:
(For question {entity_index_delimiter}1{entity_index_delimiter}, {resolution_result_delimiter}no{resolution_result_delimiter}, Product A and Product B are different products.){record_delimiter}
(For question {entity_index_delimiter}2{entity_index_delimiter}, {resolution_result_delimiter}no{resolution_result_delimiter}, Product A and Product B are different products.){record_delimiter}
(For question {entity_index_delimiter}3{entity_index_delimiter}, {resolution_result_delimiter}yes{resolution_result_delimiter}, Product A and Product B are the same product.){record_delimiter}
(For question {entity_index_delimiter}4{entity_index_delimiter}, {resolution_result_delimiter}no{resolution_result_delimiter}, Product A and Product B are different products.){record_delimiter}
#############################

Example 2:

Question:
When determining whether two toponym are the same, you should only focus on critical properties and overlook noisy factors. 

Demonstration 1: name of toponym A is : "nanjing", name of toponym B is :"nanjing city"  No, toponym A and toponym B are same toponym.
Question 1: name of toponym A is : "Chicago", name of toponym B is :"ChiTown"  
Question 2: name of toponym A is : "Shanghai", name of toponym B is :"Zhengzhou"  
Question 3: name of toponym A is : "Beijing", name of toponym B is :"Peking"
Question 4: name of toponym A is : "Los Angeles", name of toponym B is :"Cleveland" 

Use domain knowledge of toponym to help understand the text and answer the above 4 questions in the format: For Question i, Yes, toponym A and toponym B are the same toponym. or  No, toponym A and toponym B are different toponym. For Question i+1, (repeat the above procedures)
################
Output:
(For question {entity_index_delimiter}1{entity_index_delimiter}, {resolution_result_delimiter}yes{resolution_result_delimiter}, toponym A and toponym B are same toponym.){record_delimiter}
(For question {entity_index_delimiter}2{entity_index_delimiter}, {resolution_result_delimiter}no{resolution_result_delimiter}, toponym A and toponym B are different toponym.){record_delimiter}
(For question {entity_index_delimiter}3{entity_index_delimiter}, {resolution_result_delimiter}yes{resolution_result_delimiter}, toponym A and toponym B are the same toponym.){record_delimiter}
(For question {entity_index_delimiter}4{entity_index_delimiter}, {resolution_result_delimiter}no{resolution_result_delimiter}, toponym A and toponym B are different toponym.){record_delimiter}
#############################

-Real Data-
######################
Question:{input_text}
######################
Output:
"""