有没有办法将IBM的Natural Language Understanding输出转换为XML格式？

import json
import xml.etree.ElementTree as ET

# 假设您已经调用了IBM NLU API，并获得了响应结果
nlu_response = '''
{
  "usage": {
    "text_units": 1,
    "text_characters": 100,
    "features": 1
  },
  "language": "en",
  "keywords": [
    {
      "text": "IBM",
      "relevance": 0.98,
      "count": 1
    },
    {
      "text": "Natural Language Understanding",
      "relevance": 0.95,
      "count": 1
    }
  ],
  "entities": [
    {
      "type": "Company",
      "text": "IBM",
      "relevance": 0.98,
      "count": 1
    }
  ]
}
'''

# 解析JSON响应
data = json.loads(nlu_response)

# 创建XML根节点
root = ET.Element("analysis")

# 添加语言信息
language = ET.SubElement(root, "language")
language.text = data["language"]

# 添加关键字
keywords = ET.SubElement(root, "keywords")
for keyword in data["keywords"]:
    keyword_elem = ET.SubElement(keywords, "keyword")
    keyword_text = ET.SubElement(keyword_elem, "text")
    keyword_text.text = keyword["text"]
    keyword_relevance = ET.SubElement(keyword_elem, "relevance")
    keyword_relevance.text = str(keyword["relevance"])
    keyword_count = ET.SubElement(keyword_elem, "count")
    keyword_count.text = str(keyword["count"])

# 添加实体
entities = ET.SubElement(root, "entities")
for entity in data["entities"]:
    entity_elem = ET.SubElement(entities, "entity")
    entity_type = ET.SubElement(entity_elem, "type")
    entity_type.text = entity["type"]
    entity_text = ET.SubElement(entity_elem, "text")
    entity_text.text = entity["text"]
    entity_relevance = ET.SubElement(entity_elem, "relevance")
    entity_relevance.text = str(entity["relevance"])
    entity_count = ET.SubElement(entity_elem, "count")
    entity_count.text = str(entity["count"])

# 生成XML文档
xml_output = ET.tostring(root, encoding="utf-8", xml_declaration=True)
xml_string = xml_output.decode("utf-8")

# 打印XML结果
print(xml_string)