Maxent_POS_Tag_Annotator: Apache OpenNLP based POS tag annotators

Description

Generate an annotator which computes POS tag annotations using the Apache OpenNLP Maxent Part of Speech tagger.

Usage

Maxent_POS_Tag_Annotator(language = "en", probs = FALSE, model = NULL)

Arguments

language

a character string giving the ISO-639 code of the language being processed by the annotator.

probs

a logical indicating whether the computed annotations should provide the token probabilities obtained from the Maxent model as their ‘POS_prob’ feature.

model

a character string giving the path to the Maxent model file to be used, or NULL indicating to use a default model file for the given language (if available, see Details).

Value

An Annotator object giving the generated POS tag annotator.

Details

See http://opennlp.sourceforge.net/models-1.5/ for available model files. For languages other than English, these can conveniently be made available to R by installing the respective openNLPmodels.language package from the repository at https://datacube.wu.ac.at. For English, no additional installation is required.

Examples

Run this code

# NOT RUN {
require("NLP")
## Some text.
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)

## Need sentence and word token annotations.
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
## Variant with POS tag probabilities as (additional) features.
head(annotate(s, Maxent_POS_Tag_Annotator(probs = TRUE), a2))

## Determine the distribution of POS tags for word tokens.
a3w <- subset(a3, type == "word")
tags <- sapply(a3w$features, `[[`, "POS")
tags
table(tags)
## Extract token/POS pairs (all of them): easy.
sprintf("%s/%s", s[a3w], tags)

## Extract pairs of word tokens and POS tags for second sentence:
a3ws2 <- annotations_in_spans(subset(a3, type == "word"),
                              subset(a3, type == "sentence")[2L])[[1L]]
sprintf("%s/%s", s[a3ws2], sapply(a3ws2$features, `[[`, "POS"))
# }