jaring kata

Deskripsi :

WordNet adalah database leksikal bahasa Inggris yang besar. Kata benda, kata kerja, kata sifat dan kata keterangan dikelompokkan ke dalam set sinonim kognitif (synsets), masing-masing mengungkapkan konsep yang berbeda. Sinset saling terkait melalui hubungan konseptual-semantik dan leksikal.

Dokumentasi Tambahan : Jelajahi di Makalah Dengan Kode
Beranda : https://wordnet.princeton.edu/
Kode sumber : tfds.text.Wordnet
Versi :
- 0.1.0 (default): Tidak ada catatan rilis.
Ukuran unduhan : 3.99 MiB
Di-cache otomatis ( dokumentasi ): Ya
Struktur fitur :

FeaturesDict({
    'lhs': Text(shape=(), dtype=string),
    'relation': Text(shape=(), dtype=string),
    'rhs': Text(shape=(), dtype=string),
})

Dokumentasi fitur :

Fitur	Kelas	Dtype
	fiturDict
lhs	Teks	rangkaian
hubungan	Teks	rangkaian
rhs	Teks	rangkaian

Kunci yang diawasi (Lihat as_supervised doc ): None
Gambar ( tfds.show_examples ): Tidak didukung.

wordnet/WN18 (konfigurasi default)

Deskripsi konfigurasi : DATA WORDNET TENSOR ini terdiri dari kumpulan triplet (synset, relation_type, triplet) yang diekstrak dari WordNet 3.0 ( http://wordnet.princeton.edu ). Kumpulan data ini dapat dilihat sebagai tensor 3-mode yang menggambarkan hubungan ternary antar synset. Lihat https://everest.hds.utc.fr/doku.php?id=en :transe.
Ukuran dataset : 11.07 MiB
Perpecahan :

Membelah	Contoh
`'test'`	5.000
`'train'`	141.442
`'validation'`	5.000

Contoh ( tfds.as_dataframe ):

Kutipan :

@article{10.1145/219717.219748,
author = {Miller, George A.},
title = {WordNet: A Lexical Database for English},
year = {1995},
issue_date = {Nov. 1995},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {38},
number = {11},
issn = {0001-0782},
url = {https://doi.org/10.1145/219717.219748},
doi = {10.1145/219717.219748},
journal = {Commun. ACM},
month = nov,
pages = {39--41},
numpages = {3}
}

@incollection{NIPS2013_5071,
title = {Translating Embeddings for Modeling Multi-relational Data},
author = {Bordes, Antoine and Usunier, Nicolas and Garcia-Duran, Alberto and Weston, Jason and Yakhnenko, Oksana},
booktitle = {Advances in Neural Information Processing Systems 26},
editor = {C. J. C. Burges and L. Bottou and M. Welling and Z. Ghahramani and K. Q. Weinberger},
pages = {2787--2795},
year = {2013},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/5071-translating-embeddings-for-modeling-multi-relational-data.pdf}
}

wordnet/WN18RR

Deskripsi konfigurasi : Sama seperti WN18 tetapi memperbaiki kebocoran pengujian melalui hubungan terbalik. Lihat https://github.com/TimDettmers/ConvE
Ukuran dataset : 7.02 MiB
Perpecahan :

Membelah	Contoh
`'test'`	3.134
`'train'`	86.835
`'validation'`	3.034

Contoh ( tfds.as_dataframe ):

Kutipan :

@article{10.1145/219717.219748,
author = {Miller, George A.},
title = {WordNet: A Lexical Database for English},
year = {1995},
issue_date = {Nov. 1995},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {38},
number = {11},
issn = {0001-0782},
url = {https://doi.org/10.1145/219717.219748},
doi = {10.1145/219717.219748},
journal = {Commun. ACM},
month = nov,
pages = {39--41},
numpages = {3}
}

@inproceedings{dettmers2018conve,
    Author = {Dettmers, Tim and Pasquale, Minervini and Pontus, Stenetorp and Riedel, Sebastian},
    Booktitle = {Proceedings of the 32th AAAI Conference on Artificial Intelligence},
    Title = {Convolutional 2D Knowledge Graph Embeddings},
    Url = {https://arxiv.org/abs/1707.01476},
    Year = {2018},
        pages  = {1811--1818},
    Month = {February}
}