cleanNLP v1.10.0
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A Tidy Data Model for Natural Language Processing
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.
Functions in cleanNLP
| Name | Description | |
| download_core_nlp | Download java files needed for CoreNLP | |
| extract_documents | Extract documents from an annotation object | |
| get_coreference | Access coreferences from an annotation object | |
| get_dependency | Access dependencies from an annotation object | |
| get_token | Access tokens from an annotation object | |
| get_vector | Access word embedding vector from an annotation object | |
| cleanNLP-package | cleanNLP: A Tidy Data Model for Natural Language Processing | |
| combine_documents | Combine a set of annotations | |
| get_sentence | Access sentence-level annotations | |
| get_tfidf | Construct the TF-IDF Matrix from Annotation or Data Frame | |
| read_annotation | Read annotation files from disk | |
| run_annotators | Run the annotation pipeline on a set of documents | |
| init_coreNLP | Interface for initializing the coreNLP backend | |
| init_spaCy | Interface for initializing up the spaCy backend | |
| pos_frequency | Universal Part of Speech Code Frequencies | |
| print.annotation | Print a summary of an annotation object | |
| dep_frequency | Universal Dependency Frequencies | |
| doc_id_reset | Reset document ids | |
| init_tokenizers | Interface for initializing the tokenizers backend | |
| from_CoNLL | Reads a CoNLL-U or CoNLL-X File | |
| get_combine | One Table Summary of an Annotation Object | |
| get_document | Access document meta data from an annotation object | |
| get_entity | Access named entities from an annotation object | |
| obama | Annotation of Barack Obama's State of the Union Addresses | |
| tidy_pca | Compute Principal Components and store as a Data Frame | |
| to_CoNNL | Returns a CoNLL-U Document | |
| word_frequency | Most frequent English words | |
| write_annotation | Write annotation files to disk | |
| No Results! | ||
Vignettes of cleanNLP
| Name | ||
| figs/glmnet_plot.pdf | ||
| figs/glmnet_plot.png | ||
| figs/num_tokens.pdf | ||
| figs/num_tokens.png | ||
| figs/pca_plot.pdf | ||
| figs/pca_plot.png | ||
| figs/tm_sotu.pdf | ||
| figs/tm_sotu.png | ||
| case_study.Rmd | ||
| schema.Rmd | ||
| No Results! | ||
Last month downloads
Details
| Type | Package |
| SystemRequirements | Python (>= 2.7.0); spaCy |
| License | LGPL-2 |
| URL | https://statsmaths.github.io/cleanNLP/ |
| BugReports | http://github.com/statsmaths/cleanNLP/issues |
| LazyData | true |
| VignetteBuilder | knitr |
| RoxygenNote | 6.0.1 |
| NeedsCompilation | no |
| Packaged | 2017-07-01 10:38:36 UTC; taylor |
| Repository | CRAN |
| Date/Publication | 2017-07-01 14:48:49 UTC |
| suggests | covr (>= 2.2.2) , knitr (>= 1.15) , RCurl (>= 1.95) , reticulate (>= 0.7) , rJava (>= 0.9-8) , rmarkdown (>= 1.4) , testthat (>= 1.0.1) , tokenizers (>= 0.1.4) |
| imports | dplyr (>= 0.5.0) , Matrix (>= 1.2) , methods , readr (>= 1.1.0) , stats , stringi , utils |
| depends | R (>= 2.10) |
| Contributors |
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