Referensi:
paralelTweet
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:tweets_ar_en_parallel/parallelTweets')
- Keterangan :
Twitter users often post parallel tweets—tweets that contain the same content but are
written in different languages. Parallel tweets can be an important resource for developing
machine translation (MT) systems among other natural language processing (NLP) tasks. This
resource is a result of a generic method for collecting parallel tweets. Using the method,
we compiled a bilingual corpus of English-Arabic parallel tweets and a list of Twitter accounts
who post English-Arabic tweets regularly. Additionally, we annotate a subset of Twitter accounts
with their countries of origin and topic of interest, which provides insights about the population
who post parallel tweets.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.0.0
- Perpecahan :
Membelah | Contoh |
---|---|
'test' | 166706 |
- Fitur :
{
"ArabicTweetID": {
"dtype": "int64",
"id": null,
"_type": "Value"
},
"EnglishTweetID": {
"dtype": "int64",
"id": null,
"_type": "Value"
}
}
Daftar akun
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:tweets_ar_en_parallel/accountList')
- Keterangan :
Twitter users often post parallel tweets—tweets that contain the same content but are
written in different languages. Parallel tweets can be an important resource for developing
machine translation (MT) systems among other natural language processing (NLP) tasks. This
resource is a result of a generic method for collecting parallel tweets. Using the method,
we compiled a bilingual corpus of English-Arabic parallel tweets and a list of Twitter accounts
who post English-Arabic tweets regularly. Additionally, we annotate a subset of Twitter accounts
with their countries of origin and topic of interest, which provides insights about the population
who post parallel tweets.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.0.0
- Perpecahan :
Membelah | Contoh |
---|---|
'test' | 1389 |
- Fitur :
{
"account": {
"dtype": "string",
"id": null,
"_type": "Value"
}
}
anotasi topik negara
Gunakan perintah berikut untuk memuat kumpulan data ini di TFDS:
ds = tfds.load('huggingface:tweets_ar_en_parallel/countryTopicAnnotation')
- Keterangan :
Twitter users often post parallel tweets—tweets that contain the same content but are
written in different languages. Parallel tweets can be an important resource for developing
machine translation (MT) systems among other natural language processing (NLP) tasks. This
resource is a result of a generic method for collecting parallel tweets. Using the method,
we compiled a bilingual corpus of English-Arabic parallel tweets and a list of Twitter accounts
who post English-Arabic tweets regularly. Additionally, we annotate a subset of Twitter accounts
with their countries of origin and topic of interest, which provides insights about the population
who post parallel tweets.
- Lisensi : Tidak ada lisensi yang diketahui
- Versi : 1.0.0
- Perpecahan :
Membelah | Contoh |
---|---|
'test' | 200 |
- Fitur :
{
"account": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"country": {
"num_classes": 12,
"names": [
"QA",
"BH",
"AE",
"OM",
"SA",
"PL",
"JO",
"IQ",
"Other",
"EG",
"KW",
"SY"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
},
"topic": {
"num_classes": 12,
"names": [
"Gov",
"Culture",
"Education",
"Sports",
"Travel",
"Events",
"Business",
"Science",
"Politics",
"Health",
"Governoment",
"Media"
],
"names_file": null,
"id": null,
"_type": "ClassLabel"
}
}