r - Extracting noun+noun or (adj|noun)+noun from Text

Question

I would like to query if it is possible to extract noun+noun or (adj|noun)+noun in R package openNLP?That is, I would like to use linguistic filtering to extract candidate noun phrases. Could you direct me how to do? Many thanks.

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Thanks for the responses. here is the code:

library("openNLP")

acq <- "Gulf Applied Technologies Inc said it sold its subsidiaries engaged in
        pipeline and terminal operations for 12.2 mln dlrs. The company said 
        the sale is subject to certain post closing adjustments, 
        which it did not explain. Reuter." 

acqTag <- tagPOS(acq)    
acqTagSplit = strsplit(acqTag," ")
acqTagSplit

qq = 0
tag = 0

for (i in 1:length(acqTagSplit[[1]])){
    qq[i] <-strsplit(acqTagSplit[[1]][i],'/')
    tag[i] = qq[i][[1]][2]
}

index = 0

k = 0

for (i in 1:(length(acqTagSplit[[1]])-1)) {

    if ((tag[i] == "NN" && tag[i+1] == "NN") | 
        (tag[i] == "NNS" && tag[i+1] == "NNS") | 
        (tag[i] == "NNS" && tag[i+1] == "NN") | 
        (tag[i] == "NN" && tag[i+1] == "NNS") | 
        (tag[i] == "JJ" && tag[i+1] == "NN") | 
        (tag[i] == "JJ" && tag[i+1] == "NNS"))
    {      
            k = k +1
            index[k] = i
    }

}

index

---

Reader can refer index on acqTagSplit to do noun+noun or (adj|noun)+noun extractation. (The code is not optimum but work. If you have any idea, please let me know.)

Furthermore, I still have a problem.

Justeson and Katz (1995) proposed another linguistic filtering to extract candidate noun phrases:

((Adj|Noun)+|((Adj|Noun)(Noun-Prep)?)(Adj|Noun))Noun

I cannot well understand its meaning. Could you do me a favor to explain it or transform such representation into R language. Many thanks.

Answer 1

I don't have an open console on which to test this, but have your tried to tokenize with tagPOS and then grep for "noun", "noun" or perhaps paste(tagPOS(acq), collapse=".") and search for "noun.noun". Then gregexpr could be used to extract positions.

EDIT: The format of the tagged output was a bit different than I remembered. I think this method of read.table()-ing after substituting " "s for spaces is much more efficient than what I see above:

 acqdf <- read.table(textConnection(gsub(" ", "
", acqTag)), sep="/", stringsAsFactors=FALSE)
 acqdf$nnadj <- grepl("NN|JJ", acqdf$V2)
 acqdf$nnadj 
# [1]  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE  TRUE
#[16] FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE
#[31]  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE
 acqdf$nnadj[1:(nrow(acqdf)-1)] & acqdf$nnadj[2:nrow(acqdf)]
# [1]  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
#[16] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE
#[31] FALSE FALSE FALSE FALSE FALSE FALSE
 acqdf$pair <- c(NA, acqdf$nnadj[1:(nrow(acqdf)-1)] & acqdf$nnadj[2:nrow(acqdf)])
 acqdf[1:7, ]

            V1  V2 nnadj  pair
1         Gulf NNP  TRUE    NA
2      Applied NNP  TRUE  TRUE
3 Technologies NNP  TRUE  TRUE
4          Inc NNP  TRUE  TRUE
5         said VBD FALSE FALSE
6           it PRP FALSE FALSE
7         sold VBD FALSE FALSE