python编程代码，爬取豆瓣影评，构建一个简单的知识图谱，以图形数据库或三元组的形式存储。

在Python中，我们可以使用`requests`库获取网页内容，然后结合如`BeautifulSoup`解析HTML，获取影评数据。为了构建知识图谱并存储为三元组（主体、属性、值），我们通常会用到图数据库工具，比如`Neo4j`，其Python驱动程序为`neo4j-driver`。

以下是一个简化示例，展示如何从豆瓣电影页面抓取一条影评并将其存入Neo4j：

import requests
from bs4 import BeautifulSoup
from neo4j import GraphDatabase

# 设置Neo4j连接信息
URI = "bolt://localhost:7687"
USER = "neo4j"
PASSWORD = "password"

def get_html(url):
    response = requests.get(url)
    return BeautifulSoup(response.text, 'html.parser')

def parse_review(html):
    # 这里假设影评标题在<h2>标签下，评分在<span class="rating_num">中
    title = html.find('h2').text.strip()
    rating = html.find('span', {'class': 'rating_num'}).text.strip()

    return (title, '评分', rating)

def store_in_neo4j(review_data):
    driver = GraphDatabase.driver(URI, auth=(USER, PASSWORD))
    with driver.session() as session:
        session.run(
            """
            CREATE (:Movie {title: $title})-[:RATED]->(:Rating {value: $rating})
            """,
            title=review_data[0], rating=review_data[2]
        )
    driver.close()

# 示例URL
url = "https://movie.douban.com/subject/<your-movie-id>/comments"
html = get_html(url)
review = parse_review(html)
store_in_neo4j(review)