Sentences - A command line sentence tokenizer
This command line utility will convert a blob of text into a list of sentences.
Install
go get gopkg.in/neurosnap/sentences.v1
go install gopkg.in/neurosnap/sentences.v1/cmd/sentences
Binaries
Linux
Mac
Windows
Command
Get it
go get gopkg.in/neurosnap/sentences.v1
Use it
import (
"fmt"
"gopkg.in/neurosnap/sentences.v1"
"gopkg.in/neurosnap/sentences.v1/data"
)
func main() {
text := `A perennial also-ran, Stallings won his seat when longtime lawmaker David Holmes
died 11 days after the filing deadline. Suddenly, Stallings was a shoo-in, not
the long shot. In short order, the Legislature attempted to pass a law allowing
former U.S. Rep. Carolyn Cheeks Kilpatrick to file; Stallings challenged the
law in court and won. Kilpatrick mounted a write-in campaign, but Stallings won.`
b, _ := data.Asset("data/english.json");
training, _ := sentences.LoadTraining(data)
tokenizer := sentences.NewSentenceTokenizer(training)
sentences := tokenizer.Tokenize(text)
for _, s := range sentences {
fmt.Println(s.Text)
}
}
English
This package attempts to fix some problems I noticed for english.
import (
"fmt"
"gopkg.in/neurosnap/sentences.v1/english"
)
func main() {
text := "Hi there. Does this really work?"
tokenizer, err := english.NewSentenceTokenizer(nil)
if err != nil {
panic(err)
}
sentences := tokenizer.Tokenize(text)
for _, s := range sentences {
fmt.Println(s.Text)
}
}
Customizable
Sentences was built around composability, most major components of this package
can be extended.
Eager to make adhoc changes but don't know how to start?
Have a look at github.com/neurosnap/sentences/english
for a solid example.
Notice
I have not tested this tokenizer in any other language besides English. By default
the command line utility loads english. I welcome anyone willing to test the
other languages to submit updates as needed.
A primary goal for this package is to be multilingual so I'm willing to help in
any way possible.
This library is a port of the nltk's punkt tokenizer.
A Punkt Tokenizer
An unsupervised multilingual sentence boundary detection library for golang.
The way the punkt system accomplishes this goal is through training the tokenizer
with text in that given language. Once the likelyhoods of abbreviations, collocations,
and sentence starters are determined, finding sentence boundaries becomes easier.
There are many problems that arise when tokenizing text into sentences, the primary
issue being abbreviations. The punkt system attempts to determine whether a word
is an abbrevation, an end to a sentence, or even both through training the system with text
in the given language. The punkt system incorporates both token- and type-based
analysis on the text through two different phases of annotation.
Unsupervised multilingual sentence boundary detection
Performance
Using Brown Corpus which is annotated American English
text, we compare this package with other libraries across multiple programming languages.
Library | Avg Speed (s, 10 runs) | Accuracy (%) |
---|
Sentences | 1.96 | 98.95 |
NLTK | 5.22 | 99.21 |