Python jieba 文本文件“红楼梦.txt”中包含《红楼梦》小说前20章内容。对“红楼梦.txt”中的文本进行分词，并对人物名称进行归一化处理：凤姐、凤姐儿、凤丫头归一为凤姐；宝玉、二爷、宝二爷归一为宝玉；黛玉、颦儿、林妹妹、黛玉道归一为黛玉；宝钗、宝丫头归一为宝钗；贾母、老祖宗归一为贾母；袭人、袭人道归一为袭人；贾政、贾政道归一为贾政；贾琏、琏二爷归一为贾琏。提取出场次数不少于40次的人物名称，将人物名称及其出场次数按照递减排序写入out.txt文件中。

可以使用Python中的jieba库进行文本分词，然后使用字典进行人物名称归一化处理，最后统计人物出场次数并按照递减排序输出至文件。

以下是代码实现：

import jieba

# 读取文本文件
with open("红楼梦.txt", "r", encoding="utf-8") as f:
    text = f.read()

# 分词
words = jieba.lcut(text)

# 人物名称归一化处理
mapping = {
    "凤姐儿": "凤姐",
    "凤丫头": "凤姐",
    "二爷": "宝玉",
    "宝二爷": "宝玉",
    "颦儿": "黛玉",
    "林妹妹": "黛玉",
    "黛玉道": "黛玉",
    "宝丫头": "宝钗",
    "老祖宗": "贾母",
    "袭人道": "袭人",
    "贾政道": "贾政",
    "琏二爷": "贾琏"
}
normalized_words = []
for word in words:
    if word in mapping:
        word = mapping[word]
    normalized_words.append(word)

# 统计人物出场次数
count = {}
for name in ["贾宝玉", "林黛玉", "薛宝钗", "贾母", "王熙凤", "史湘云", "妙玉", "元春", "贾琏", "李纨", "贾环", "贾兰", "贾蓉", "贾芸", "贾珠", "秦可卿", "晴雯", "袭人", "贾政"]:
    count[name] = normalized_words.count(name)

# 按照递减排序并输出至文件
with open("out.txt", "w", encoding="utf-8") as f:
    for name, freq in sorted(count.items(), key=lambda x: x[1], reverse=True):
        if freq >= 40:
            f.write(name + " " + str(freq) + "\n")

运行以上代码后，会生成一个名为“out.txt”的文件，里面包含了人物名称及其出场次数。