dep_frequency

The language-specific frequency of universal dependency codes as given
in standard treebank corpora. Frequencies are multiplied by 100.

data

Provides a set of fast tools for converting a textual corpus into a set of normalized tables. Users may make use of a Python back end with 'spaCy' <https://spacy.io> or the Java back end 'CoreNLP' <http://stanfordnlp.github.io/CoreNLP/>. A minimal back end with no external dependencies is also provided. Exposed annotation tasks include tokenization, part of speech tagging, named entity recognition, entity linking, sentiment analysis, dependency parsing, coreference resolution, and word embeddings. Summary statistics regarding token unigram, part of speech tag, and dependency type frequencies are also included to assist with analyses.

Taylor Arnold

cleanNLP

dep_frequency: Universal Dependency Frequencies

Description

Arguments

References