In my dataset I am trying to create variables containing the number of nouns, verbs and adjectives, respectively for each observation. Using the openNLP package I have managed to get this far:
s <- paste(c("Pierre Vinken, 61 years old, will join the board as a ",
"nonexecutive director Nov. 29.\n",
"Mr. Vinken is chairman of Elsevier N.V., ",
"the Dutch publishing group."),
collapse = "")
s <- as.String(s)
s
sent_token_annotator <- Maxent_Sent_Token_Annotator()
word_token_annotator <- Maxent_Word_Token_Annotator()
a2 <- annotate(s, list(sent_token_annotator, word_token_annotator))
pos_tag_annotator <- Maxent_POS_Tag_Annotator()
pos_tag_annotator
a3 <- annotate(s, pos_tag_annotator, a2)
a3
a3w <- subset(a3, type == "word")
a3w
This gives me the output:
id type start end features
1 sentence 1 84 constituents=<<integer,18>>
2 sentence 86 153 constituents=<<integer,13>>
3 word 1 6 POS=NNP
4 word 8 13 POS=NNP
5 word 14 14 POS=,
And so on.
My question is, how do I extract for example the number of nouns per observation so I can use this for further analysis.
Thanks!
I don't use openNLP
, but use different packages for POS tagging. If someone has an answer for openNLP
that can help you that would be great.
But I will give you a solution using udpipe
. You might find it useful.
s <- paste(c("Pierre Vinken, 61 years old, will join the board as a ",
"nonexecutive director Nov. 29.\n",
"Mr. Vinken is chairman of Elsevier N.V., ",
"the Dutch publishing group."),
collapse = "")
library(udpipe)
if (file.exists("english-ud-2.0-170801.udpipe"))
ud_model <- udpipe_load_model(file = "english-ud-2.0-170801.udpipe") else {
ud_model <- udpipe_download_model(language = "english")
ud_model <- udpipe_load_model(ud_model$file_model)
}
x <- udpipe_annotate(ud_model, s)
x <- as.data.frame(x)
table(x$upos)
ADJ ADP AUX DET NOUN NUM PROPN PUNCT VERB
2 2 2 3 6 2 8 5 1
edit: counts per sentence:
table(x$sentence_id, x$upos)
ADJ ADP AUX DET NOUN NUM PROPN PUNCT VERB
1 2 1 1 2 3 2 3 3 1
2 0 1 1 1 3 0 5 2 0
When you create a data.frame from x after the annotations, you have access to doc_id, paragraph_id, sentence_id, etc etc. You can create a whole range of statistics per document / sentence etc. The vignettes give a good overview of what is possible.