SADiLaR Language Resource Repository
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536 research outputs found
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Morphologically annotated corpus for Sepedi
Full text linkNCHLT corpus of morphologically annotated tokens in Sepedi converted to the tags used during phases 1 and 2 of the SADiLaR-II project.
The data is given as txt files. Each line consists of a token and the corresponding morphological analysis, tab separated.
The file for Sepedi contains a total of 73,031 tokens. All the data has been automatically converted, then manually checked and re-annotated where necessary by linguistic experts as well as quality controlled. Please see the included protocol for more details on the morphological tags used
Morphologically annotated corpus for isiXhosa
No full textNCHLT corpus of morphologically annotated tokens in isiXhosa converted to the tags used during phases 1 and 2 of the SADiLaR-II project.
The data is given as txt files. Each line consists of a token and the corresponding morphological analysis, tab separated.
The file for isiXhosa contains a total of approximately 46,465 tokens. All the data has been automatically converted, then manually checked and re-annotated where necessary by linguistic experts as well as quality controlled. Please see the included protocol for more details on the morphological tags used
Morphologically annotated corpus for Xitsonga
No full textNCHLT corpus of morphologically annotated tokens in Xitsonga converted to the tags used during phases 1 and 2 of the SADiLaR-II project.
The data is given as txt files. Each line consists of a token and the corresponding morphological analysis, tab separated.
The file for Xitsonga contains a total of 69,584 tokens. All the data has been automatically converted, then manually checked and re-annotated where necessary by linguistic experts as well as quality controlled. Please see the included protocol for more details on the morphological tags used
Morphologically annotated corpus for Sesotho
No full textNCHLT corpus of morphologically annotated tokens in Sesotho converted to the tags used during phases 1 and 2 of the SADiLaR-II project.
The data is given as txt files. Each line consists of a token and the corresponding morphological analysis, tab separated.
The file for Sesotho contains a total of 73,727 tokens. All the data has been automatically converted, then manually checked and re-annotated where necessary by linguistic experts as well as quality controlled. Please see the included protocol for more details on the morphological tags used
Morphologically annotated corpus for Siswati
Full text linkNCHLT corpus of morphologically annotated tokens in Siswati converted to the tags used during phases 1 and 2 of the SADiLaR-II project.
The data is given as txt files. Each line consists of a token and the corresponding morphological analysis, tab separated.
The file for Siswati contains a total of 43,568 tokens. All the data has been automatically converted, then manually checked and re-annotated where necessary by linguistic experts as well as quality controlled. Please see the included protocol for more details on the morphological tags used
NCHLT isiZulu FLAIR-backward embeddings
No full textContextual word/string embeddings for the backward flavour of the FLAIR architecture (Akbik et al., 2018). The embedding provides real-valued vector representations for isiZulu text
NCHLT Xitsonga fastText-CBoW embeddings
No full textStatic word and subword embeddings for the continuous bag of words (CBoW) flavour of the fastText architecture (Bojanowski et al., 2017). The embedding provides real-valued vector representations for Xitsonga text
NCHLT Sesotho FLAIR-backward embeddings
No full textContextual word/string embeddings for the backward flavour of the FLAIR architecture (Akbik et al., 2018). The embedding provides real-valued vector representations for Sesotho text
NCHLT Setswana word2vec-Skipgram embeddings
No full textStatic word embeddings for the Skipgram flavour of the word2vec (w2v) architecture (Mikolov et al., 2013). The embedding provides real-valued vector representations for Setswana text
NCHLT isiNdebele FLAIR-forward embeddings
No full textContextual word/string embeddings for the forward flavour of the FLAIR architecture (Akbik et al., 2018). The embedding provides real-valued vector representations for isiNdebele text