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import copy |
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import json |
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import os |
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import re |
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from collections import Counter |
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from pprint import pprint |
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from shutil import copy2, rmtree |
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from zipfile import ZIP_DEFLATED, ZipFile |
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from tqdm import tqdm |
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ontology = { |
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"domains": { |
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"景点": { |
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"description": "查找景点", |
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"slots": { |
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"名称": { |
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"description": "景点名称", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"门票": { |
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"description": "景点门票价格", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"游玩时间": { |
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"description": "景点游玩时间", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"评分": { |
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"description": "景点评分", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"地址": { |
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"description": "景点地址", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"电话": { |
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"description": "景点电话", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边景点": { |
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"description": "景点周边景点", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边餐馆": { |
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"description": "景点周边餐馆", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边酒店": { |
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"description": "景点周边酒店", |
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"is_categorical": False, |
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"possible_values": [] |
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} |
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} |
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}, |
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"餐馆": { |
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"description": "查找餐馆", |
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"slots": { |
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"名称": { |
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"description": "餐馆名称", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"推荐菜": { |
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"description": "餐馆推荐菜", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"人均消费": { |
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"description": "餐馆人均消费", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"评分": { |
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"description": "餐馆评分", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"地址": { |
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"description": "餐馆地址", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"电话": { |
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"description": "餐馆电话", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"营业时间": { |
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"description": "餐馆营业时间", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边景点": { |
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"description": "餐馆周边景点", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边餐馆": { |
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"description": "餐馆周边餐馆", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边酒店": { |
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"description": "餐馆周边酒店", |
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"is_categorical": False, |
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"possible_values": [] |
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} |
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} |
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}, |
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"酒店": { |
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"description": "查找酒店", |
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"slots": { |
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"名称": { |
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"description": "酒店名称", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"酒店类型": { |
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"description": "酒店类型", |
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"is_categorical": True, |
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"possible_values": [ |
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'高档型', '豪华型', '经济型', '舒适型' |
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] |
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}, |
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"酒店设施": { |
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"description": "酒店设施", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"价格": { |
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"description": "酒店价格", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"评分": { |
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"description": "酒店评分", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"地址": { |
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"description": "酒店地址", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"电话": { |
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"description": "酒店电话", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边景点": { |
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"description": "酒店周边景点", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边餐馆": { |
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"description": "酒店周边餐馆", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"周边酒店": { |
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"description": "酒店周边酒店", |
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"is_categorical": False, |
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"possible_values": [] |
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} |
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} |
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}, |
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"地铁": { |
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"description": "乘坐地铁从某地到某地", |
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"slots": { |
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"出发地": { |
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"description": "地铁出发地", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"目的地": { |
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"description": "地铁目的地", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"出发地附近地铁站": { |
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"description": "出发地附近地铁站", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"目的地附近地铁站": { |
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"description": "目的地附近地铁站", |
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"is_categorical": False, |
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"possible_values": [] |
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} |
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} |
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}, |
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"出租": { |
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"description": "乘坐出租车从某地到某地", |
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"slots": { |
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"出发地": { |
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"description": "出租出发地", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"目的地": { |
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"description": "出租目的地", |
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"is_categorical": False, |
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"possible_values": [] |
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}, |
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"车型": { |
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"description": "出租车车型", |
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"is_categorical": True, |
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"possible_values": [ |
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"#CX" |
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] |
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}, |
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"车牌": { |
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"description": "出租车车牌", |
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"is_categorical": True, |
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"possible_values": [ |
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"#CP" |
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] |
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} |
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} |
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}, |
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"General": { |
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"description": "通用领域", |
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"slots": {} |
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} |
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}, |
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"intents": { |
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"Inform": { |
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"description": "告知相关属性" |
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}, |
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"Request": { |
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"description": "询问相关属性" |
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}, |
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"Recommend": { |
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"description": "推荐搜索结果" |
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}, |
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"Select": { |
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"description": "在附近搜索" |
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}, |
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"NoOffer": { |
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"description": "未找到符合用户要求的结果" |
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}, |
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"bye": { |
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"description": "再见" |
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}, |
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"thank": { |
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"description": "感谢" |
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}, |
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"welcome": { |
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"description": "不客气" |
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}, |
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"greet": { |
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"description": "打招呼" |
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}, |
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}, |
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"state": { |
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"景点": { |
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"名称": "", |
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"门票": "", |
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"游玩时间": "", |
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"评分": "", |
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"周边景点": "", |
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"周边餐馆": "", |
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"周边酒店": "", |
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}, |
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"餐馆": { |
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"名称": "", |
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"推荐菜": "", |
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"人均消费": "", |
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"评分": "", |
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"周边景点": "", |
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"周边餐馆": "", |
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"周边酒店": "", |
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}, |
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"酒店": { |
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"名称": "", |
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"酒店类型": "", |
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"酒店设施": "", |
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"价格": "", |
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"评分": "", |
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"周边景点": "", |
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"周边餐馆": "", |
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"周边酒店": "", |
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}, |
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"地铁": { |
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"出发地": "", |
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"目的地": "", |
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}, |
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"出租": { |
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"出发地": "", |
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"目的地": "", |
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} |
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}, |
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"dialogue_acts": { |
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"categorical": {}, |
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"non-categorical": {}, |
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"binary": {} |
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} |
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} |
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cnt_domain_slot = Counter() |
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def convert_da(da_list, utt): |
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''' |
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convert dialogue acts to required format |
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:param da_dict: list of (intent, domain, slot, value) |
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:param utt: user or system utt |
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''' |
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global ontology, cnt_domain_slot |
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converted_da = { |
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'categorical': [], |
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'non-categorical': [], |
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'binary': [] |
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} |
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for intent, domain, slot, value in da_list: |
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if intent == 'NoOffer': |
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assert slot == 'none' and value == 'none' |
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converted_da['binary'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': '' |
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}) |
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elif intent == 'General': |
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assert slot == 'none' and value == 'none' |
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converted_da['binary'].append({ |
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'intent': domain, |
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'domain': intent, |
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'slot': '' |
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}) |
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elif intent == 'Request': |
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assert value == '' and slot != 'none' |
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converted_da['binary'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': slot |
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}) |
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elif '酒店设施' in slot: |
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converted_da['binary'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': f"{slot}-{value}" |
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}) |
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elif intent == 'Select': |
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assert slot == '源领域' |
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converted_da['binary'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': f"{slot}-{value}" |
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}) |
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elif slot in ['酒店类型', '车型', '车牌']: |
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assert intent in ['Inform', 'Recommend'] |
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assert slot != 'none' and value != 'none' |
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converted_da['categorical'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': slot, |
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'value': value |
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}) |
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else: |
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assert intent in ['Inform', 'Recommend'] |
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assert slot != 'none' and value != 'none' |
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matches = utt.count(value) |
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if matches == 1: |
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start = utt.index(value) |
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end = start + len(value) |
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converted_da['non-categorical'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': slot, |
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'value': value, |
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'start': start, |
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'end': end |
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}) |
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cnt_domain_slot['have span'] += 1 |
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else: |
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converted_da['non-categorical'].append({ |
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'intent': intent, |
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'domain': domain, |
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'slot': slot, |
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'value': value |
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}) |
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cnt_domain_slot['no span'] += 1 |
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return converted_da |
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def transform_user_state(user_state): |
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goal = [] |
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for subgoal in user_state: |
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gid, domain, slot, value, mentioned = subgoal |
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if len(value) != 0: |
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t = 'inform' |
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else: |
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t = 'request' |
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if len(goal) < gid: |
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goal.append({domain: {'inform': {}, 'request': {}}}) |
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goal[gid-1][domain][t][slot] = [value, 'mentioned' if mentioned else 'not mentioned'] |
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return goal |
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def preprocess(): |
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original_data_dir = '../../crosswoz' |
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new_data_dir = 'data' |
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os.makedirs(new_data_dir, exist_ok=True) |
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for filename in os.listdir(os.path.join(original_data_dir,'database')): |
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copy2(f'{original_data_dir}/database/{filename}', new_data_dir) |
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global ontology |
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dataset = 'crosswoz' |
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splits = ['train', 'validation', 'test'] |
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dialogues_by_split = {split: [] for split in splits} |
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for split in ['train', 'val', 'test']: |
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data = json.load(ZipFile(os.path.join(original_data_dir, f'{split}.json.zip'), 'r').open(f'{split}.json')) |
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if split == 'val': |
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split = 'validation' |
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for ori_dialog_id, ori_dialog in data.items(): |
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dialogue_id = f'{dataset}-{split}-{len(dialogues_by_split[split])}' |
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goal = {'inform': {}, 'request': {}} |
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goal["description"] = '\n'.join(ori_dialog["task description"]) |
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cur_domains = [x[1] for i, x in enumerate(ori_dialog['goal']) if i == 0 or ori_dialog['goal'][i-1][1] != x[1]] |
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dialogue = { |
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'dataset': dataset, |
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'data_split': split, |
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'dialogue_id': dialogue_id, |
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'original_id': ori_dialog_id, |
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'domains': cur_domains, |
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'goal': goal, |
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'user_state_init': transform_user_state(ori_dialog['goal']), |
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'type': ori_dialog['type'], |
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'turns': [], |
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'user_state_final': transform_user_state(ori_dialog['final_goal']) |
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} |
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for turn_id, turn in enumerate(ori_dialog['messages']): |
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if ori_dialog_id == '2660' and turn_id in [8,9]: |
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continue |
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elif ori_dialog_id == '7467' and turn_id in [14,15]: |
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continue |
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elif ori_dialog_id == '11726' and turn_id in [4,5]: |
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continue |
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elif ori_dialog_id == '10550' and turn_id == 6: |
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dialogue['user_state_final'] = dialogue['turns'][-2]['user_state'] |
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break |
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elif ori_dialog_id == '11724' and turn_id == 8: |
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dialogue['user_state_final'] = dialogue['turns'][-2]['user_state'] |
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break |
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speaker = 'user' if turn['role'] == 'usr' else 'system' |
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utt = turn['content'] |
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das = turn['dialog_act'] |
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dialogue_acts = convert_da(das, utt) |
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dialogue['turns'].append({ |
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'speaker': speaker, |
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'utterance': utt, |
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'utt_idx': len(dialogue['turns']), |
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'dialogue_acts': dialogue_acts, |
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}) |
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for da_type in dialogue_acts: |
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das = dialogue_acts[da_type] |
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for da in das: |
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ontology["dialogue_acts"][da_type].setdefault((da['intent'], da['domain'], da['slot']), {}) |
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ontology["dialogue_acts"][da_type][(da['intent'], da['domain'], da['slot'])][speaker] = True |
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if speaker == 'user': |
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dialogue['turns'][-1]['user_state'] = transform_user_state(turn['user_state']) |
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else: |
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belief_state = turn['sys_state_init'] |
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for domain in belief_state: |
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belief_state[domain].pop('selectedResults') |
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dialogue['turns'][-2]['state'] = belief_state |
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db_query = turn['sys_state'] |
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db_results = {} |
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for domain in list(db_query.keys()): |
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db_res = db_query[domain].pop('selectedResults') |
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if len(db_res) > 0: |
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db_results[domain] = [{'名称': x} for x in db_res] |
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else: |
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db_query.pop(domain) |
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dialogue['turns'][-1]['db_query'] = db_query |
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dialogue['turns'][-1]['db_results'] = db_results |
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dialogues_by_split[split].append(dialogue) |
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pprint(cnt_domain_slot.most_common()) |
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dialogues = [] |
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for split in splits: |
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dialogues += dialogues_by_split[split] |
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for da_type in ontology['dialogue_acts']: |
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ontology["dialogue_acts"][da_type] = sorted([str( |
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{'user': speakers.get('user', False), 'system': speakers.get('system', False), 'intent': da[0], |
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'domain': da[1], 'slot': da[2]}) for da, speakers in ontology["dialogue_acts"][da_type].items()]) |
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json.dump(dialogues[:10], open(f'dummy_data.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) |
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json.dump(ontology, open(f'{new_data_dir}/ontology.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) |
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json.dump(dialogues, open(f'{new_data_dir}/dialogues.json', 'w', encoding='utf-8'), indent=2, ensure_ascii=False) |
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with ZipFile('data.zip', 'w', ZIP_DEFLATED) as zf: |
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for filename in os.listdir(new_data_dir): |
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zf.write(f'{new_data_dir}/{filename}') |
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rmtree(new_data_dir) |
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return dialogues, ontology |
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|
|
|
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def fix_entity_booked_info(entity_booked_dict, booked): |
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for domain in entity_booked_dict: |
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if not entity_booked_dict[domain] and booked[domain]: |
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entity_booked_dict[domain] = True |
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booked[domain] = [] |
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return entity_booked_dict, booked |
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|
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|
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if __name__ == '__main__': |
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preprocess() |