allennlp.data.dataset_readers.universal_dependencies_multilang

class allennlp.data.dataset_readers.universal_dependencies_multilang.UniversalDependenciesMultiLangDatasetReader(languages: List[str], token_indexers: Dict[str, allennlp.data.token_indexers.token_indexer.TokenIndexer] = None, use_language_specific_pos: bool = False, lazy: bool = False, alternate: bool = True, is_first_pass_for_vocab: bool = True, instances_per_file: int = 32)[source]

Bases: allennlp.data.dataset_readers.dataset_reader.DatasetReader

Reads multiple files in the conllu Universal Dependencies format. All files should be in the same directory and the filenames should have the language identifier followed by a dash as a prefix (e.g. en-universal.conll) When using the alternate option, the reader alternates randomly between the files every instances_per_file. The is_first_pass_for_vocab disables this behaviour for the first pass (could be useful for a single full path over the dataset in order to generate a vocabulary).

Notice: when using the alternate option, one should also use the instances_per_epoch option for the iterator. Otherwise, each epoch will loop infinitely.

Parameters
languagesList[str], required

The language identifiers to use.

token_indexersDict[str, TokenIndexer], optional (default=``{“tokens”: SingleIdTokenIndexer()}``)

The token indexers to be applied to the words TextField.

use_language_specific_posbool, optional (default = False)

Whether to use UD POS tags, or to use the language specific POS tags provided in the conllu format.

alternatebool, optional (default = True)

Whether to alternate between input files.

is_first_pass_for_vocabbool, optional (default = True)

Whether the first pass will be for generating the vocab. If true, the first pass will run over the entire dataset of each file (even if alternate is on).

instances_per_fileint, optional (default = 32)

The amount of consecutive cases to sample from each input file when alternating.

text_to_instance(self, lang:str, words:List[str], upos_tags:List[str], dependencies:List[Tuple[str, int]]=None) → allennlp.data.instance.Instance[source]
Parameters
langstr, required.

The language identifier.

wordsList[str], required.

The words in the sentence to be encoded.

upos_tagsList[str], required.

The universal dependencies POS tags for each word.

dependencies ``List[Tuple[str, int]]``, optional (default = None)

A list of (head tag, head index) tuples. Indices are 1 indexed, meaning an index of 0 corresponds to that word being the root of the dependency tree.

Returns
An instance containing words, upos tags, dependency head tags and head
indices as fields. The language identifier is stored in the metadata.
allennlp.data.dataset_readers.universal_dependencies_multilang.get_file_paths(pathname:str, languages:List[str])[source]

Gets a list of all files by the pathname with the given language ids. Filenames are assumed to have the language identifier followed by a dash as a prefix (e.g. en-universal.conll).

Parameters
pathnamestr, required.

An absolute or relative pathname (can contain shell-style wildcards)

languagesList[str], required

The language identifiers to use.

Returns
A list of tuples (language id, file path).