Corpus class initialization

Corpora indexed using the Corpus Workbench (CWB) offer an efficient data structure for large, linguistically annotated corpora. The corpus-class keeps basic information on a CWB corpus. Corresponding to the name of the class, the corpus-method is the initializer for objects of the corpus class. A CWB corpus can also be hosted remotely on an OpenCPU server. The remote_corpus class (which inherits from the corpus class) will handle respective information. A (limited) set of polmineR functions and methods can be executed on the corpus on the remote machine from the local R session by calling them on the remote_corpus object. Calling the corpus-method without an argument will return a data.frame with basic information on the corpora that are available.

# S4 method for character
corpus(.Object, server = NULL, restricted)

# S4 method for missing
corpus()

Arguments

.Object	The upper-case ID of a CWB corpus stated by a length-one character vector.
server	If NULL (default), the corpus is expected to be present locally. If provided, the name of an OpenCPU server (can be an IP address) that hosts a corpus, or several corpora. The corpus-method will then instantiate a remote_corpus object.
restricted	A logical value, whether access to a remote corpus is restricted (TRUE) or not (FALSE).

Details

Calling corpus() will return a data.frame listing the corpora available locally and described in the active registry directory, and some basic information on the corpora.

A corpus object is instantiated by passing a corpus ID as argument .Object. Following the conventions of the Corpus Workbench (CWB), Corpus IDs are written in upper case. If .Object includes lower case letters, the corpus object is instantiated nevertheless, but a warning is issued to prevent bad practice. If .Object is not a known corpus, the error message will include a suggestion if there is a potential candidate that can be identified by agrep.

A limited set of methods of the polmineR package is exposed to be executed on a remote OpenCPU server. As a matter of convenience, the whereabouts of an OpenCPU server hosting a CWB corpus can be stated in an environment variable "OPENCPU_SERVER". Environment variables for R sessions can be set easily in the .Renviron file. A convenient way to do this is to call usethis::edit_r_environ().

Slots

corpus

A length-one character vector, the upper-case ID of a CWB corpus.

data_dir

The directory where the files for the indexed corpus are.

type

The type of the corpus (e.g. "plpr" for a corpus of plenary protocols).

name

An additional name for the object that may be more telling than the corpus ID.

encoding

The encoding of the corpus, given as a length-one character vector.

size

Number of tokens (size) of the corpus, a length-one integer vector.

server

The URL (can be IP address) of the OpenCPU server. The slot is available only with the remote_corpus class inheriting from the corpus class.

user

If the corpus on the server requires authentication, the username.

password

If the corpus on the server requires authentication, the password.

See also

Methods to extract basic information from a corpus object are covered by the corpus-methods documentation object. Use the s_attributes method to get information on structural attributes. Analytical methods available for corpus objects are size, count, dispersion, kwic, cooccurrences, as.TermDocumentMatrix.

Other classes to manage corpora: phrases, regions, subcorpus

Examples

use("polmineR")
#> ... activating corpus: GERMAPARLMINI (version: 0.0.1 | build date: 2019-02-23)
#> ... activating corpus: REUTERS

# get corpora present locally
y <- corpus()

# initialize corpus object
r <- corpus("REUTERS")
r <- corpus ("reuters") # will work, but will result in a warning
#> Warning: Using corpus 'REUTERS', not 'reuters' - note that corpus ids are expected to be in upper case throughout.


# apply core polmineR methods
a <- size(r)
b <- s_attributes(r)
c <- count(r, query = "oil")
d <- dispersion(r, query = "oil", s_attribute = "id")
e <- kwic(r, query = "oil")
f <- cooccurrences(r, query = "oil")

# used corpus initialization in a pipe
y <- corpus("REUTERS") %>% s_attributes()
y <- corpus("REUTERS") %>% count(query = "oil")

# working with a remote corpus
if (FALSE) {
REUTERS <- corpus("REUTERS", server = Sys.getenv("OPENCPU_SERVER"))
count(REUTERS, query = "oil")
size(REUTERS)
kwic(REUTERS, query = "oil")

GERMAPARL <- corpus("GERMAPARL", server = Sys.getenv("OPENCPU_SERVER"))
s_attributes(GERMAPARL)
size(x = GERMAPARL)
count(GERMAPARL, query = "Integration")
kwic(GERMAPARL, query = "Islam")

p <- partition(GERMAPARL, year = 2000)
s_attributes(p, s_attribute = "year")
size(p)
kwic(p, query = "Islam", meta = "date")

GERMAPARL <- corpus("GERMAPARLMINI", server = Sys.getenv("OPENCPU_SERVER"))
s_attrs <- s_attributes(GERMAPARL, s_attribute = "date")
sc <- subset(GERMAPARL, date == "2009-11-10")
}