flair.datasets.biomedical.HUNER_SPECIES#
- class flair.datasets.biomedical.HUNER_SPECIES(sentence_splitter=None)View on GitHub#
Bases:
HunerMultiCorpus
Union of all HUNER species data sets.
- __init__(sentence_splitter=None)View on GitHub#
Initializes a MultiCorpus by concatenating splits from individual corpora.
- Parameters:
corpora (list[Corpus]) – List of Corpus objects to combine.
task_ids (Optional[list[str]], optional) – List of string IDs for each corpus/task. If None, generates default IDs like “Task_0”, “Task_1”. Defaults to None.
name (str, optional) – Name for the combined corpus. Defaults to “multicorpus”.
**corpusargs – Additional arguments passed to the parent Corpus constructor (e.g., sample_missing_splits).
Methods
__init__
([sentence_splitter])Initializes a MultiCorpus by concatenating splits from individual corpora.
add_label_noise
(label_type, labels[, ...])Adds artificial label noise to a specified split (in-place).
downsample
([percentage, downsample_train, ...])Randomly downsample the corpus to the given percentage (by removing data points).
filter_empty_sentences
()A method that filters all sentences consisting of 0 tokens.
filter_long_sentences
(max_charlength)A method that filters all sentences for which the plain text is longer than a specified number of characters.
get_all_sentences
()Returns all sentences (spanning all three splits) in the
Corpus
.get_label_distribution
()Counts occurrences of each label in the corpus and returns them as a dictionary object.
make_label_dictionary
(label_type[, ...])Creates a Dictionary for a specific label type from the corpus.
make_tag_dictionary
(tag_type)DEPRECATED: Creates tag dictionary ensuring 'O', '<START>', '<STOP>'.
make_vocab_dictionary
([max_tokens, min_freq])Creates a
Dictionary
of all tokens contained in the corpus.obtain_statistics
([label_type, pretty_print])Print statistics about the corpus, including the length of the sentences and the labels in the corpus.
Attributes
dev
The dev split as a
torch.utils.data.Dataset
object.test
The test split as a
torch.utils.data.Dataset
object.train
The training split as a
torch.utils.data.Dataset
object.