Referanslar:
yaklaşık
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ca')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 372665 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
de
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/de')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 547578 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
es
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/es')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 386699 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
fi
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/fi')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 387465 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
MERHABA
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/hi')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 401648 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
İD
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/id')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 463862 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
evet
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ko')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 560105 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
Bayan
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ms')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 528181 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
lütfen
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/pl')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 623267 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ru
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ru')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 551770 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
efendim
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/sr')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 559423 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
TL
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/tl')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 160750 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
vi
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/vi')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 351643 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ar
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ar')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 339109 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
CS
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/cs')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 564462 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
el
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/el')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 446052 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ve
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/et')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 87023 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
Fr
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/fr')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 418411 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
saat
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/hr')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 629667 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
BT
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/it')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 378325 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
lt
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/lt')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 848018 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
nl
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/nl')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 520664 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
puan
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/pt')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 396773 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
Sk
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/sk')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 500135 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
sv
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/sv')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 634881 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
TR
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/tr')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 607324 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
zh
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/zh')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 1570853 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
bg
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/bg')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 559694 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
da
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/da')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 546440 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
tr
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/en')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 423982 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
fa
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/fa')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 492903 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
O
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/he')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 459933 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ha
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/hu')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 590218 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
evet
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ja')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 1691018 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
seviye
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/lv')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 331568 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
HAYIR
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/no')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 552176 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
ro
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/ro')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 285985 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
sl
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/sl')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 521251 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
o
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/th')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 217631 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
İngiltere
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/uk')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 561373 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}
kombine
Bu veri kümesini TFDS'ye yüklemek için aşağıdaki komutu kullanın:
ds = tfds.load('huggingface:polyglot_ner/combined')
- Tanım :
Polyglot-NER
A training dataset automatically generated from Wikipedia and Freebase the task
of named entity recognition. The dataset contains the basic Wikipedia based
training data for 40 languages we have (with coreference resolution) for the task of
named entity recognition. The details of the procedure of generating them is outlined in
Section 3 of the paper (https://arxiv.org/abs/1410.3791). Each config contains the data
corresponding to a different language. For example, "es" includes only spanish examples.
- Lisans : Bilinen lisans yok
- Sürüm : 1.0.0
- Bölünmeler :
Bölmek | Örnekler |
---|---|
'train' | 21070925 |
- Özellikler :
{
"id": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"lang": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"words": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
},
"ner": {
"feature": {
"dtype": "string",
"id": null,
"_type": "Value"
},
"length": -1,
"id": null,
"_type": "Sequence"
}
}