def preprocess_prediction_data(data, tokenizer):
    """
    It process the prediction data as the format used as training.

    Args:
        data (obj:`List[List[str, str]]`): 
            The prediction data whose each element is a text pair. 
            Each text will be tokenized by jieba.lcut() function.
        tokenizer(obj: paddlenlp.data.JiebaTokenizer): It use jieba to cut the chinese string.

    Returns:
        examples (obj:`list`): The processed data whose each element 
            is a `list` object, which contains 

            - query_ids(obj:`list[int]`): The list of query ids.
            - title_ids(obj:`list[int]`): The list of title ids.
            - query_seq_len(obj:`int`): The input sequence query length.
            - title_seq_len(obj:`int`): The input sequence title length.

    """
    examples = []
    for query, title in data:
        query_ids = tokenizer.encode(query)
        title_ids = tokenizer.encode(title)
        examples.append([query_ids, title_ids, len(query_ids), len(title_ids)])
    return examples