Transpose Query result in sql server
I've created a quick model:

USE tempdb;
IF EXISTS (SELECT 1 FROM sys.schemas s WHERE s.name = 'wde')
BEGIN
    DROP TABLE wde.INTERACCION;
    DROP TABLE wde.TIPIFICACION;
    DROP TABLE wde.DICCIONARIO;
    DROP SCHEMA wde;
END
GO
CREATE SCHEMA wde;
GO
CREATE TABLE wde.INTERACCION (ID int);
CREATE TABLE wde.TIPIFICACION (ID int, CODIGO int);
CREATE TABLE wde.DICCIONARIO (CODEID int, [DESCRIPTION] varchar(100), [PARENT] varchar(100), [LEVEL] int, CODIGOID int);

INSERT INTO wde.INTERACCION (ID) VALUES (59);
INSERT INTO wde.TIPIFICACION (ID, CODIGO) VALUES (59,1);
INSERT INTO wde.DICCIONARIO(CODEID, DESCRIPTION,PARENT,LEVEL,CODIGOID) 
VALUES (100, 'MARCA VEHICULO'       , 0  , 1, 1)
    , (101, 'SUCURSAL'              , 0  , 1, 1)
    , (102, 'CONTACTADO'            , 0  , 1, 1)
    , (105, 'FIAT'                  , 100, 2, 1)
    , (117, 'ECUADOR'               , 101, 2, 1)
    , (122, 'CONTACTO TELEFONICO'   , 102, 2, 1);


This query gets the results you want, but may only be valid for your limited set of test data shown.  Without more specific requirements from you, it's difficult to be concise.

SELECT i.ID
    , Level1 = STUFF((SELECT ', ' + d.DESCRIPTION 
        FROM wde.DICCIONARIO d 
            INNER JOIN wde.TIPIFICACION t ON d.CODIGOID = t.CODIGO 
        WHERE t.ID = i.ID AND d.PARENT = 0 FOR XML PATH('')),  1, 2, '')
    , Level2 = STUFF((SELECT ', ' + d.DESCRIPTION 
        FROM wde.DICCIONARIO d 
            INNER JOIN wde.TIPIFICACION t ON d.CODIGOID = t.CODIGO 
        WHERE t.ID = i.ID AND d.PARENT &lt;&gt; 0 FOR XML PATH('')),  1, 2, '')
FROM wde.INTERACCION i;


Results:


╔════╦══════════════════════════════════════╦════════════════════════════════════╗
║ ID ║                Level1                ║               Level2               ║
╠════╬══════════════════════════════════════╬════════════════════════════════════╣
║ 59 ║ MARCA VEHICULO, SUCURSAL, CONTACTADO ║ FIAT, ECUADOR, CONTACTO TELEFONICO ║
╚════╩══════════════════════════════════════╩════════════════════════════════════╝