从字符串列表中,确定哪些是人名,哪些不是

Question

我有一个类似下面的矢量,并希望确定列表中的哪些元素是人名,哪些不是.我发现了humaniformat包,它格式化了名称,但遗憾的是并不确定字符串是否实际上是一个名称.我还发现了一些用于实体提取的包,但它们似乎需要实际的文本来进行词性标注,而不是单个名称.

例

pkd.names.quotes <- c("Mr. Rick Deckard", # Name
                      "Do Androids Dream of Electric Sheep", # Not a name
                      "Roy Batty", # Name 
                      "How much is an electric ostrich?", # Not a name
                      "My schedule for today lists a six-hour self-accusatory depression.", # Not a name
                      "Upon him the contempt of three planets descended.", # Not a name
                      "J.F. Sebastian", # Name
                      "Harry Bryant", # Name
                      "goat class", # Not a name
                      "Holden, Dave", # Name
                      "Leon Kowalski", # Name
                      "Dr. Eldon Tyrell") # Name

Answer 1

这是一种方法.美国人口普查局将其数据库中出现的姓氏列表(频率)列表> 100次:全部152,000个.如果使用完整列表,则所有字符串都有一个名称.例如,"class","him"和"the"是某些语言的名称(不知道哪种语言).同样,有许多名字列表(见本文).

下面的代码抓住了2000年人口普查中的所有姓氏,并列出了引用的帖子中的名字,然后是每个列表中最常见的10,000个子集,组合并清理列表,并将其用作tm包中的字典识别哪些字符串包含名称.您可以通过更改freq变量来控制"灵敏度" (freq = 10,000似乎可以生成您想要的结果).

url <- "http://www2.census.gov/topics/genealogy/2000surnames/names.zip"
tf <- tempfile()
download.file(url,tf, mode="wb")                     # download archive of surname data
files    <- unzip(tf, exdir=tempdir())               # unzips and returns a vector of file names
surnames <- read.csv(files[grepl("\\.csv$",files)])  # 152,000 surnames occurring >100 times
url <- "http://deron.meranda.us/data/census-derived-all-first.txt"
firstnames <- read.table(url(url), header=FALSE)
freq <- 10000
dict  <- unique(c(tolower(surnames$name[1:freq]), tolower(firstnames$V1[1:freq])))
library(tm)
corp <- Corpus(VectorSource(pkd.names.quotes))
tdm  <- TermDocumentMatrix(corp, control=list(tolower=TRUE, dictionary=dict))
m    <- as.matrix(tdm)
m    <- m[rowSums(m)>0,]
m
#            Docs
# Terms       1 2 3 4 5 6 7 8 9 10 11 12
#   bryant    0 0 0 0 0 0 0 1 0  0  0  0
#   dave      0 0 0 0 0 0 0 0 0  1  0  0
#   deckard   1 0 0 0 0 0 0 0 0  0  0  0
#   eldon     0 0 0 0 0 0 0 0 0  0  0  1
#   harry     0 0 0 0 0 0 0 1 0  0  0  0
#   kowalski  0 0 0 0 0 0 0 0 0  0  1  0
#   leon      0 0 0 0 0 0 0 0 0  0  1  0
#   rick      1 0 0 0 0 0 0 0 0  0  0  0
#   roy       0 0 1 0 0 0 0 0 0  0  0  0
#   sebastian 0 0 0 0 0 0 1 0 0  0  0  0
#   tyrell    0 0 0 0 0 0 0 0 0  0  0  1
which(colSums(m)>0)
#  1  3  7  8 10 11 12