Coercion functions to and from tokens objects, checks for whether an object is a tokens object, and functions to combine tokens objects.
as.tokens(x, concatenator = "_", ...)# S3 method for list
as.tokens(x, concatenator = "_", ...)
# S3 method for spacyr_parsed
as.tokens(x, concatenator = "/",
include_pos = c("none", "pos", "tag"), use_lemma = FALSE, ...)
# S3 method for tokens
as.list(x, ...)
# S3 method for tokens
as.character(x, use.names = FALSE, ...)
is.tokens(x)
# S3 method for tokens
unlist(x, recursive = FALSE, use.names = TRUE)
# S3 method for tokens
+(t1, t2)
# S3 method for tokens
c(...)
object to be coerced or checked
character between multi-word expressions, default is the underscore character. See Details.
character; whether and which part-of-speech tag to use:
"none"
do not use any part of speech indicator, "pos"
use the
pos
variable, "tag"
use the tag
variable. The POS
will be added to the token after "concatenator"
.
logical; if TRUE
, use the lemma rather than the raw
token
logical; preserve names if TRUE
. For
as.character
and unlist
only.
tokens one to be added
tokens two to be added
as.tokens
returns a quanteda tokens object.
as.list
returns a simple list of characters from a
tokens object.
as.character
returns a character vector from a
tokens object.
is.tokens
returns TRUE
if the object is of class
tokens, FALSE
otherwise.
unlist
returns a simple vector of characters from a
tokens object.
c(...)
and +
return a tokens object whose documents
have been added as a single sequence of documents.
The concatenator
is used to automatically generate dictionary
values for multi-word expressions in tokens_lookup
and
dfm_lookup
. The underscore character is commonly used to join
elements of multi-word expressions (e.g. "piece_of_cake", "New_York"), but
other characters (e.g. whitespace " " or a hyphen "-") can also be used.
In those cases, users have to tell the system what is the concatenator in
your tokens so that the conversion knows to treat this character as the
inter-word delimiter, when reading in the elements that will become the
tokens.
# NOT RUN {
# create tokens object from list of characters with custom concatenator
dict <- dictionary(list(country = "United States",
sea = c("Atlantic Ocean", "Pacific Ocean")))
lis <- list(c("The", "United-States", "has", "the", "Atlantic-Ocean",
"and", "the", "Pacific-Ocean", "."))
toks <- as.tokens(lis, concatenator = "-")
tokens_lookup(toks, dict)
# combining tokens
toks1 <- tokens(c(doc1 = "a b c d e", doc2 = "f g h"))
toks2 <- tokens(c(doc3 = "1 2 3"))
toks1 + toks2
c(toks1, toks2)
# }
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