我在 nlu.md 文件中添加了以下话语:
## intent:input_year
- [2019](year)
并有这样的故事:
## test
* input_year{"year" : "2019"}
- utter_year
意图input_year
和操作utter_year
被添加到 domain.yml
我通过命令行训练了一个新模型,启动了 rasa x 并与机器人交谈,在输入2019
识别的意图时是null0
.
这是我的管道:
pipeline:
- name: "SpacyNLP"
- name: "SpacyTokenizer"
- name: "RegexFeaturizer"
- name: "SpacyFeaturizer"
- name: "CRFEntityExtractor"
- name: "EntitySynonymMapper"
- name: "SklearnIntentClassifier"
- name: "DucklingHTTPExtractor"
# url of the running duckling server
url: "http://localhost:8000"
# dimensions to extract
dimensions: ["email", "time", "number", "amount-of-money", "distance"]
# allows you to configure the locale, by default the language is
# used
locale: "NL_Nothing"
# if not set the default timezone of Duckling is going to be used
# needed to calculate dates from relative expressions like "tomorrow"
timezone: "US/Pacific"
这是训练新数据的有效方法吗?还是使用 UI 进行训练很重要?请提出这里有什么问题。谢谢