tnf: Learnable Name Finder

In news-r/decipher: Natural Language Processing tools for R

Description

Learnable Name Finder

Usage

tnf_(model, sentences, output = NULL)

tnf(model, sentences)

Arguments

model	Model to use, generally returned by tnf_train or tnf_train.
sentences	Sentences containing entities to find, a character vector or full path to file, usually .txt.
output	An output file, generally .txt.

Details

name tagging:

• <END>. is invalid

• <END> . is valid

Use check_tags

Value

Full path to the output if specified.

Examples

## Not run: 
# get working directory
# need to pass full path
wd <- getwd()

# Training to find "WEF"
data <- paste("This organisation is called the <START:wef> World Economic Forum <END>",
  "It is often referred to as <START:wef> Davos <END> or the <START:wef> WEF <END> .")

# train the model
model <- tnf_train(model = paste0(wd, "/wef.bin"), lang = "en",
  data = data, type = "wef")

# Create sentences to test our model
sentences <- paste("This sentence mentions the World Economic Forum the annual meeting",
  "of which takes place in Davos. Note that the forum is often called the WEF.")

# run model on sentences
results <- tnf(model = model, sentences = sentences)

# same with text files
# Save the above as file
write(data, file = "input.txt")

# Trains the model and returns the full path to the model
model <- tnf_train_(model = paste0(wd, "/wef.bin"), lang = "en",
  data = paste0(wd, "/input.txt"), type = "wef")

# Create sentences to test our model
sentences <- paste("This sentence mentions the World Economic Forum the annual meeting",
  "of which takes place in Davos. Note that the forum is often called the WEF.")

# Save sentences
write(data, file = "sentences.txt")

# Extract names
# Without specifying an output file the extracted names appear in the console
tnf(model = model, sentences = paste0(wd, "/sentences.txt"))

# returns path to output file
output <- tnf_(model = model, sentences = paste0(wd, "/sentences.txt"),
  output = paste0(wd, "/output.txt"))

## End(Not run)

news-r/decipher documentation built on July 19, 2019, 5:58 p.m.