Question

我有一个像

这样的数据框

Task    Response

1   NA
2   NA
3   EFFICACY
4   I was sent to external vendor for solution (PDA parts), but at PDA parts they identified within few minites that new battery would not solve the issue. I wonder why this diagnosis part could no have been done at the locla IS service in the Amgen office. Now I spent time to visit PDA parts at their place, while this finally did not bring any solution.
5   Issue could not be resolved

其中2列是任务和响应。并且响应具有一定的NA值。

现在我正在寻找为每条记录创建POS标记并仅提取NOUNS

5条记录创建的POS标记应该与 -

相同

Task   POSTagged
1      NA/NNP

2      NA/NNP
3      EFFICACY/NNP
4       vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN
5      Issue/NN

所以它应该是2列和5条记录的矩阵

我正在尝试使用该功能

tagPOS =  function(x) {
  s <- as.String(x)

  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()
  a3 = annotate(s, pos_tag_annotator, a2)
  a3w = subset(a3, type == "word")
  POStags = unlist(lapply(a3w$features, `[[`, "POS"))
  gc()
  return(paste(POStags,collapse = " "))
}

我尝试了lapply，并通过遍历记录但是所有人都为每条记录提供了所有5条记录的组合POStag。

即。对于每条记录，我将POS标记为

NA/NNP NA/NNP EFFICACY/NNP vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN Issue/NN

我得到的是

Task Response
1   NA/NNP NA/NNP EFFICACY/NNP vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN Issue/NN
2   NA/NNP NA/NNP EFFICACY/NNP vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN Issue/NN

3   NA/NNP NA/NNP EFFICACY/NNP vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN Issue/NN

4   NA/NNP NA/NNP EFFICACY/NNP vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN Issue/NN

5   NA/NNP NA/NNP EFFICACY/NNP vendor/NN solution/NN PDA/NN parts/NNS PDA/NNP parts/NNS minites/NNS battery/NN issue/NN diagnosis/NN part/NN locla/NN service/NN Amgen/NNP office/NN time/NN PDA/NNP parts/NNS place/NN solution/NN Issue/NN

这不是我想要的。代码尝试了

lapply(df2$Task, tagPOS (df2$Response), data = df2)
resultset <- group_by(df2, Task) %>% do(tagPOS (df2$Response))
df2[,c("Keywords"):= tagPOS(strip(df2$Response)),by = Task]
Responsedf<-lapply(Response, extractPOS, "NN")
df2$noun <- with(df2, extractPOS(df2$Response, "NN"))

但到目前为止没有任何效果希望我有道理。

任何建议都将不胜感激

Answer 1

找到解决方案 -

for (i in 0:nrow(df2)) {
  df2$noun[i]<-lapply(df2$short_description[i], extractPOS, "NN")
  gc()
}

感谢。

R中每条记录的POS标记

1 个答案: