我使用 DIETClassifier 进行实体提取，这是我的管道：
pipeline:
- name: SpacyNLP
model: en_core_web_sm
- name: SpacyTokenizer
- name: CountVectorsFeaturizer
- name: CRFEntityExtractor
- name: DIETClassifier
epochs: 200
random_seed: 2
这是我对 nlu 文件中的实体的意图示例：
version: "2.0"
nlu:
- intent: flight_search_intent
examples: |
- I want to [travel](Search_flight)
- I want a travel [ticket](Search_flight)
- I want a [flight](Search_flight) ticket
- find a [flight](Search_flight) for me please
- find a [flight](Search_flight) for me, please
- Can you please find a [flight](Search_flight) ticket for me?
- I want to book a [flight](Search_flight) ticket
- I want to book a [ticket](Search_flight)
- Can you please find a [flight](Search_flight) for me?
- I want to book a [flight](Search_flight) asap
- I want to book a [flight](Search_flight)
- I am looking for a [flight](Search_flight)
- find a [flight](Search_flight) for me
- I wanna to [travel](Search_flight)
- I need a [trip](Search_flight)
# 2) flight_search_intent_with_daeparture_and_destenation_cities_and_departure_date:
- intent: flight_search_intent_with_daeparture_and_destenation_cities_and_departure_date
examples: |
- I am looking for a [flight](Search_flight) from [Arrabury]{"entity": "city", "role": "departure"} to [Annaba]{"entity": "city", "role": "destination"} [Tomorrow](departure_date).
- I want to book a [flight](Search_flight) from [Dammam]{"entity": "city", "role": "departure"} to [Jeddah]{"entity": "city", "role": "destination"} on [14/05/2022](departure_date).
- I want to book a [flight](Search_flight) from [Berlin]{"entity": "city", "role": "departure"} to [San Francisco]{"entity": "city", "role": "destination"} on [30/1/2021](departure_date).
- Can you please find a [flight](Search_flight) for me from [Al Madinah]{"entity": "city", "role": "departure"} to [Abha]{"entity": "city", "role": "destination"} on [3-4-2020](departure_date).
- Book a [flight](Search_flight) from [Al Kharj]{"entity": "city", "role": "departure"} to [Bonthe]{"entity": "city", "role": "destination"} [Today](departure_date).
- Book a [flight](Search_flight) from [Colombo]{"entity": "city", "role": "departure"} to [Paris]{"entity": "city", "role": "destination"} on [January,21st,2020](departure_date).
- find a [flight](Search_flight) for me from [Berlin]{"entity": "city", "role": "departure"} to [San Francisco]{"entity": "city", "role": "destination"} on [January,21st,2020](departure_date).
- I want to [fly](Search_flight) from [Berlin]{"entity": "city", "role": "departure"} to [San Francisco]{"entity": "city", "role": "destination"} on [17th January 2021](departure_date).
- I wanna [trp](Search_flight) from [Berlin]{"entity": "city", "role": "departure"} to [San Francisco]{"entity": "city", "role": "destination"} on [17th January 2021](departure_date).
- I need a [flight](Search_flight) from [Berlin]{"entity": "city", "role": "departure"} to [San Francisco]{"entity": "city", "role": "destination"} [Tomorrow](departure_date).
这是我的故事的例子：
#1) Flight serch function stories:
- story: flight_search_function_story_1
steps:
- intent: greet
- action: utter_greet
- intent: flight_search_intent
- action: utter_ask_about_trip_kind
- intent: provide_round_trip
- action: utter_ask_about_departure_city
- intent: provide_departure_city
- action: utter_ask_about_departure_date
- intent: provide_date
- action: utter_ask_about_destination_city
- intent: provide_destination_city
- action: utter_ask_about_return_date
- intent: provide_date
- action: utter_suitable choices
- action: utter_something_else
- intent: thanking
- action: utter_welcome_thanks
- intent: goodbye
- action: utter_goodbye
这是我的域文件的一部分，我在其中列出了所有意图、实体和响应：
version: "2.0"
intents:
- afternoon
- morning
- provide_date
- nice_to_meet
- provide_destination_city
- get_Kind_of_cities
- waiting
- get_weather
- greet
- goodbye
- goodnight
- welcome_thanks
- provide_one_way_trip
- nice_to_talk
- askingAboutDoingWithName
- askingAboutDoingWithOutName
- flight_search_intent_with_daeparture_and_destenation_cities_only
- flight_search_with_destenation_only
- flight_search_intent
- provide_email
- flight_search_intent_with_daeparture_and_destenation_cities_and_departure_date
- provide_departure_city
- evening
- see_again
- bot_challenge
- provide_issue_deatils
- user_waiting
- well_done
- sorry
- get_Hoppies
- thanking
- flight_search_with_departure_only
- provide_round_trip
- provide_name
- provide_phone_number
- Connect_agent
- place_to_visit
entities:
- return_date
- phone
- provide_name
- get_issue_details
- weather_type
- round_flight
- report_issue
- one_way_flight
- hobby
- return_decision
- city_type
- Search_flight
- email
- departure_date
- name
- city:
roles:
- departure
- destination
responses:
utter_greet:
- text: "Hi I am Tickie! How can I help you?"
utter_cheer_up:
- text: "Here is something to cheer you up:"
image: "https://i.imgur.com/nGF1K8f.jpg"
utter_did_that_help:
- text: "Did that help you?"
但是，当我用命令训练我的聊天机器人并用rasa train命令对其进行测试时rasa shell，它只给出来自用户（我）的第一个输入的响应，然后响应停止工作！我发现错误和解决方案 2 周，但我没有找到，这是一个例子：
有人能帮我吗？或者，如果我在上面提到的文件中有任何错误，有人可以告诉我错误是什么吗？我遵循域文件的 rasa 文档以及如何在意图中定义实体，但我遇到了这个问题，我在互联网上找到的所有解释都不是 rasa 2.0，所以我不知道问题出在哪里
但是，当我从域文件中删除实体时，它有响应！但就是这样：
它说将实体添加到域文件中，正如我之前向您展示的那样，当我添加它们时，响应停止工作