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kbenoit avatar kbenoit commented on May 24, 2024

Thanks for the analysis! With respect to the sentence tokenization: Sentence tokenization is far from an exact science, and in tokenize(x, what = "sentence") we have stuck to a more standard definition of sentence (backed by the ICU boundaries definitions) that defines a sentence as a full stop . followed by a sequence of words starting with a capitalised word.

From this standpoint, tokenize() works much better than the older segment(x, what = "sentence"):

> hardText <- c("will.i.am is a rap name.",  
+               "Mr. Smith goes to Washington, D.C. on the 9.45 train.",
+               "Segmentation is hard etc. etc. for Authors et. al. to get right.",
+               "The U.N. is based in New York.")
> tokenize(hardText, what = "sentence")
[[1]]
[1] "will.i.am is a rap name."

[[2]]
[1] "Mr. Smith goes to Washington, D.C. on the 9.45 train."

[[3]]
[1] "Segmentation is hard etc. etc. for Authors et. al. to get right."

[[4]]
[1] "The U.N. is based in New York."

attr(,"class")
[1] "tokenizedTexts" "list"          
> segment(hardText, what = "sentence")
[[1]]
[1] "will."             "i."                "am is a rap name."

[[2]]
[1] "Mr Smith goes to Washington, D." "C."                              "on the 9.45 train."             

[[3]]
[1] "Segmentation is hard etc." "etc."                      "for Authors et."           "al."                      
[5] "to get right."            

[[4]]
[1] "The U."                "N."                    "is based in New York."

from quanteda.

angeloklin avatar angeloklin commented on May 24, 2024

Thanks for the reply.
I got some other error with sentence with the dfm() function, but I will open another thread for that a bit later. Have to move along with the project as the due date is always near.

Cheers

from quanteda.

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