fathyshalab/massive_social-de-DE

---
dataset_info:
features:
- name: id
dtype: string
- name: locale
dtype: string
- name: partition
dtype: string
- name: scenario
dtype:
class_label:
names:
'0': social
'1': transport
'2': calendar
'3': play
'4': news
'5': datetime
'6': recommendation
'7': email
'8': iot
'9': general
'10': audio
'11': lists
'12': qa
'13': cooking
'14': takeaway
'15': music
'16': alarm
'17': weather
- name: intent
dtype:
class_label:
names:
'0': datetime_query
'1': iot_hue_lightchange
'2': transport_ticket
'3': takeaway_query
'4': qa_stock
'5': general_greet
'6': recommendation_events
'7': music_dislikeness
'8': iot_wemo_off
'9': cooking_recipe
'10': qa_currency
'11': transport_traffic
'12': general_quirky
'13': weather_query
'14': audio_volume_up
'15': email_addcontact
'16': takeaway_order
'17': email_querycontact
'18': iot_hue_lightup
'19': recommendation_locations
'20': play_audiobook
'21': lists_createoradd
'22': news_query
'23': alarm_query
'24': iot_wemo_on
'25': general_joke
'26': qa_definition
'27': social_query
'28': music_settings
'29': audio_volume_other
'30': calendar_remove
'31': iot_hue_lightdim
'32': calendar_query
'33': email_sendemail
'34': iot_cleaning
'35': audio_volume_down
'36': play_radio
'37': cooking_query
'38': datetime_convert
'39': qa_maths
'40': iot_hue_lightoff
'41': iot_hue_lighton
'42': transport_query
'43': music_likeness
'44': email_query
'45': play_music
'46': audio_volume_mute
'47': social_post
'48': alarm_set
'49': qa_factoid
'50': calendar_set
'51': play_game
'52': alarm_remove
'53': lists_remove
'54': transport_taxi
'55': recommendation_movies
'56': iot_coffee
'57': music_query
'58': play_podcasts
'59': lists_query
- name: text
dtype: string
- name: annot_utt
dtype: string
- name: worker_id
dtype: string
- name: slot_method
sequence:
- name: slot
dtype: string
- name: method
dtype: string
- name: judgments
sequence:
- name: worker_id
dtype: string
- name: intent_score
dtype: int8
- name: slots_score
dtype: int8
- name: grammar_score
dtype: int8
- name: spelling_score
dtype: int8
- name: language_identification
dtype: string
- name: label_name
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 129790
num_examples: 391
- name: validation
num_bytes: 22472
num_examples: 68
- name: test
num_bytes: 34107
num_examples: 106
download_size: 70328
dataset_size: 186369
---
# Dataset Card for "massive_social-de-DE"

[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

原始信息汇总

数据集概述

数据集名称

"massive_social-de-DE"

数据集特征

• id: 字符串类型
• locale: 字符串类型
• partition: 字符串类型
• scenario: 分类标签，包括：social, transport, calendar, play, news, datetime, recommendation, email, iot, general, audio, lists, qa, cooking, takeaway, music, alarm, weather
• intent: 分类标签，包括：datetime_query, iot_hue_lightchange, transport_ticket, takeaway_query, qa_stock, general_greet, recommendation_events, music_dislikeness, iot_wemo_off, cooking_recipe, qa_currency, transport_traffic, general_quirky, weather_query, audio_volume_up, email_addcontact, takeaway_order, email_querycontact, iot_hue_lightup, recommendation_locations, play_audiobook, lists_createoradd, news_query, alarm_query, iot_wemo_on, general_joke, qa_definition, social_query, music_settings, audio_volume_other, calendar_remove, iot_hue_lightdim, calendar_query, email_sendemail, iot_cleaning, audio_volume_down, play_radio, cooking_query, datetime_convert, qa_maths, iot_hue_lightoff, iot_hue_lighton, transport_query, music_likeness, email_query, play_music, audio_volume_mute, social_post, alarm_set, qa_factoid, calendar_set, play_game, alarm_remove, lists_remove, transport_taxi, recommendation_movies, iot_coffee, music_query, play_podcasts, lists_query
• text: 字符串类型
• annot_utt: 字符串类型
• worker_id: 字符串类型
• slot_method: 序列类型，包括：
  • slot: 字符串类型
  • method: 字符串类型
• judgments: 序列类型，包括：
  • worker_id: 字符串类型
  • intent_score: 8位整型
  • slots_score: 8位整型
  • grammar_score: 8位整型
  • spelling_score: 8位整型
  • language_identification: 字符串类型
• label_name: 字符串类型
• label: 64位整型

数据集分割

• train: 391个样本，占用129790字节
• validation: 68个样本，占用22472字节
• test: 106个样本，占用34107字节

数据集大小

• 下载大小: 70328字节
• 数据集总大小: 186369字节