languages:
- hr
licenses:
- cc-by-sa-4.0
task_categories:
- structure-prediction
task_ids:
- tokenization
- normalization
- part-of-speech-tagging
- lemmatization
- named-entity-recognition
The hr500k training corpus contains about 500,000 Croatian tokens manually annotated on the levels of tokenisation, sentence segmentation, morphosyntactic tagging, lemmatisation and named entities.
On the sentence level, the dataset contains 20159 training samples, 1963 validation samples and 2672 test samples across the respective data splits. Each sample represents a sentence and includes the following features: sentence ID ('sent_id'), sentence text ('text'), list of tokens ('tokens'), list of lemmas ('lemmas'), list of Multext-East tags ('xpos_tags), list of UPOS tags ('upos_tags'), list of morphological features ('feats'), and list of IOB tags ('iob_tags'). A subset of the data also contains universal dependencies ('ud') and consists of 7498 training samples, 649 validation samples, and 742 test samples.
Three dataset configurations are available, namely 'ner', 'upos', and 'ud', with the corresponding features encoded as class labels. If the configuration is not specified, it defaults to 'ner'.