User:Wei2912
My name is Wei En and I'm currently a GCI student. My blog is at http://wei2912.github.io.
I decided to help out at Apertium because I find the work here quite interesting and I believe Apertium will benefit many.
The following are projects related to Apertium.
Wiktionary Crawler
https://github.com/wei2912/WiktionaryCrawler is a crawler for Wiktionary which aims to extract data from pages. It was created for a GCI task which you can read about at Task ideas for Google Code-in/Scrape inflection information from Wiktionary.
The crawler crawls a starting category (usually Category:XXX language)for subcategories, then crawls these subcategories for pages. It then passes the page to language-specific parsers which turn it into the Speling format.
The current languages supported are Chinese (zh), Thai (th) and Lao (lo). You are welcome to contribute to this project.
Spaceless Segmentation
Spaceless Segmentation has been merged into Apertium under https://svn.code.sf.net/p/apertium/svn/branches/tokenisation. It serves to tokenize languages without any whitespace. More information can be found under Task ideas for Google Code-in/Tokenisation for spaceless orthographies.
The tokeniser looks for possible tokenisations in the corpus text and selects the tokenisation which tokens appears the most in corpus.
A report comparing the above method, LRLM and RLLM (longest left to right matching and longest right to left matching respectively) is available at https://www.dropbox.com/sh/57wtof3gbcbsl7c/AABI-Mcw2E-c942BXxsMbEAja
Conversion of PDF dictionary to lttoolbox format
NOTE: This document is a draft.
In this example we're converting the following PDF file: http://home.uchicago.edu/straughn/sakhadic.pdf
We copy the text directly from the PDF file, as PDF to text converters are currently unable to convert the text properly (thanks to the arcane PDF format).
All of this preprocessing is contained in this script which we supply a filename to.
#!/bin/bash cat $1 | perl -wpne 's/•//g; s/^\d+$//g; s/=//g; s/\; /\n/g; s/cf\./cf/;' > $1.new
After the preprocessing, we get the following file:
... blank lines omitted ... аа exc. Oh! See! ааҕыс v. to reckon with аайы a. each, every күн аайы every day ...
The blank lines weren't removed so that you can tell when a page starts and end, and hence coordinate the manual processing with the dictionary.
Unfortunately for us, our preprocessor replaces "; " with "\n" in order to get a list of words seperated by newlines. Definitions may be seperated by "; " too, or spread over to the next line. Hence, we'll need to merge these lines together to get the same format as the dictionary.
Some words have different word forms. To handle this, we copy over the original word to create a new entry. This:
албас a. cunning; n. trick, ruse
becomes
албас a. cunning албас n. trick, ruse
The good part about this is that they're also seperated by "; " and will be placed on a newline after the preprocessing, so it's easy to spot the lines where we need to handle this.
The final format for each entry looks similar to this:
word1, word2 abbrv1. abbrv2. abbrv3. definition1, definition2, definition3; definition4
Words and definitions are seperated by either commas or semicolons. Abbreviations are seperated by whitespace and indicated with the use of ".".
We pass the filename of our dictionary file to this script:
#!/usr/bin/python3
import fileinput
import itertools
import re
import xml.etree.cElementTree as ET
BRACKETS_RE = re.compile(r'(\(.+?\)|\[.+?\])')
SPLIT_RE = re.compile(r'[;,]\s+')
ABBRVS = {
'a.': ['adj'],
'adv.': ['adv'],
# arch. archaic
# cf. see also
# comp. computer-related
# conv. converb, modifying verb
# dial. dialect
'det.': ['det'],
# Evk. Evenki
'exc.': ['ij'],
'int.': ['itg'],
# Mongo. Mongolian
'n.': ['n'],
'num.': ['det', 'qnt'],
# ono. onomatopoeia
'pl.': ['pl'],
'pp.': ['post'],
'pro.': ['prn'],
# Russ. Russian
'v.': ['v', 'TD']
}
class Entry(object):
def __find_brackets(self, line):
brackets = BRACKETS_RE.search(line)
if brackets:
return brackets.groups()
def __split(self, line):
return SPLIT_RE.split(line)
def __init__(self, line):
tags = line.split()
self.words = []
self.abbrvs = []
self.meanings = []
found_abbrv = False
found_conv = False
for tag in tags:
if tag in ABBRVS.keys(): # abbreviations
found_abbrv = True
self.abbrvs.extend(ABBRVS[tag])
continue
elif tag == "conv.":
found_abbrv = True
found_conv = True
self.abbrvs.append("vaux")
continue
if not found_abbrv: # entrys
self.words.append(tag)
else: # translated
self.meanings.append(tag)
# if there's "cf" in a word, we trim off everything else
for i, word in enumerate(self.words):
if word == "cf":
self.words = self.words[:i]
if found_conv:
self.words = self.words[-1]
else:
self.words = " ".join(self.words)
self.meanings = " ".join(self.meanings)
# preprocessing to place stuff
# we can't parse in comments
if not self.abbrvs:
self.words = None
self.abbrvs = None
self.meanings = None
return
# remove the brackets
brackets = self.__find_brackets(self.words)
if brackets:
for bracket in brackets:
self.words = self.words.replace(bracket, "")
brackets = self.__find_brackets(self.meanings)
if brackets:
for bracket in brackets:
self.meanings = self.meanings.replace(bracket, "")
# preprocessing meanings
self.meanings = self.meanings.replace("to", "")
# split up meanings and entrys
self.words = [x.strip() for x in self.__split(self.words)]
self.meanings = [x.strip() for x in self.__split(self.meanings)]
def insert_blanks(element, line):
words = line.split()
if not words:
return
element.text = words[0]
element.tail = None
blank = None
for i in words[1:]:
blank = ET.SubElement(element, 'b')
blank.tail = i
def main():
dictionary = ET.Element("dictionary")
pardefs = ET.SubElement(dictionary, "pardefs")
for line in fileinput.input():
line = line.strip()
if not line:
continue
comment = ET.Comment(text=line)
pardefs.append(comment)
entry = Entry(line)
if not (entry.words and entry.abbrvs and entry.meanings):
continue
for word, meaning in itertools.product(entry.words, entry.meanings):
e = ET.SubElement(pardefs, "e")
e.set('r', 'LR')
p = ET.SubElement(e, 'p')
## add word and meaning
left = ET.SubElement(p, 'l')
insert_blanks(left, word)
right = ET.SubElement(p, 'r')
insert_blanks(right, meaning)
# add abbreviations
for abbrv in entry.abbrvs:
s = ET.Element('s')
s.set('n', abbrv)
left.append(s)
right.append(s)
ET.dump(dictionary)
main()
This will give us a XML dump of the dictionary, converted to the lttoolbox format. We format the XML file as shown here:
$ xmllint --format --encode utf8 file.xml > file.dix
The `--encode utf8` option prevents `xmllint` from escaping our unicode.
The final file format looks like this:
<?xml version="1.0" encoding="utf8"?>
<dictionary>
<pardefs>
<!--аа exc. Oh! See!-->
<e r="LR">
<p>
<l>аа<s n="ij"/></l>
<r>Oh!<b/>See!<s n="ij"/></r>
</p>
</e>
<!--ааҕыс v. to reckon with-->
<e r="LR">
<p>
<l>ааҕыс<s n="v"/><s n="TD"/></l>
<r>reckon<b/>with<s n="v"/><s n="TD"/></r>
</p>
</e>
<!--аайы a. each, every-->
<e r="LR">
<p>
<l>аайы<s n="adj"/></l>
<r>each<s n="adj"/></r>
</p>
</e>
...
