def METHOD_NAME(sparql_client: PySparqlClient, affected_property_iris: list):
    # Construct query to retrieve below information for each affected property from KG
    # NOTE for this iteration, we assume that the property value estimation is already computed if the derivation is created
    # - market value (mv) IRI
    query = f"""{pda_iris.PREFIX_RDF} {pda_iris.PREFIX_RDFS}
            SELECT DISTINCT ?property ?mv
            WHERE {{
                VALUES ?property {{ <{'> <'.join(affected_property_iris)}> }}
                ?property <{iris.OBE_HASMARKETVALUE}> ?mv.
            }}"""
    # Remove unnecessary whitespaces
    query = ' '.join(query.split())
    logger.info(f"Query to retrieve property info: {query}")
    response = sparql_client.performQuery(query)
    logger.info(f"Length of response: {len(response)}")
    # Rearrange response into a dictionary where the information for each property are grouped together
    # Target format of the dictionary:
    # {
    #     "property": {
    #         'mv': iri,
    #     },
    #     ... (other properties)
    # }
    property_info_dct = {}
    property_lst = dal.get_unique_values_in_list_of_dict(response, 'property')
    for property_iri in property_lst:
        property_info_dct[property_iri] = {}
        sub_response = dal.get_sublist_in_list_of_dict_matching_key_value(response, 'property', property_iri)
        # it will be assigned as None if the key is not found
        property_info_dct[property_iri]['mv'] = dal.get_the_unique_value_in_list_of_dict(sub_response, 'mv')
    return property_info_dct