flair.datasets.relation_extraction.RE_ENGLISH_TACRED#
- class flair.datasets.relation_extraction.RE_ENGLISH_TACRED(base_path=None, in_memory=True, **corpusargs)View on GitHub#
Bases:
ColumnCorpus
- __init__(base_path=None, in_memory=True, **corpusargs)View on GitHub#
TAC Relation Extraction Dataset.
with 41 relations from https://nlp.stanford.edu/projects/tacred/. Manual download is required for this dataset.
Methods
__init__
([base_path, in_memory])TAC Relation Extraction Dataset.
add_label_noise
(label_type, labels[, ...])Generates uniform label noise distribution in the chosen dataset split.
downsample
([percentage, downsample_train, ...])Randomly downsample the corpus to the given percentage (by removing data points).
extract_and_convert_to_conllu
(data_file, ...)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 of all labels assigned to the sentences in the corpus.
make_tag_dictionary
(tag_type)Create a tag dictionary of a given label type.
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.- extract_and_convert_to_conllu(data_file, data_folder)View on GitHub#