I have some data in Chinese and Japanese, and I want it possible to search by their romanizations (Pinyin for Chinese, Romaji for Japanese). Assume that the romanizations are already provided, separated by syllables.
eg. the text "示例文本", which romanizes to ["shi", "li", "wen", "ben"].
Users should be able to match this by typing
whole syllables, with or without space, eg. shi li wen ben or shiliwenben
initials or first few letters of syllables, eg. shlwb or slwb
they might also type only part of the string, eg. wenben or wb (these examples correspond to the last two syllables of the text above).
Is there an elegant way of implementing this?
(note: I did not specify any programming language in this question, because I want to implement this in different languages. If your response is language-specific or requires specific libraries, please make it clear. Thank you!)
Related
I am currently working with MS LUIS.ai.
My string/utterance contains both English and Chinese.
Here is the problem:
While if sentence is ALL in English, it works fine in LUIS. The reason is probably because a sentence is composed of different words, which are split by a "space".
However, in Chinese (Both Traditional and Simplified), a sentence is composed of words that are concanated/joined together and difficult to be split.
For example, in English I can write:
I love you so much: There are 5 words here. In LUIS I can select I love you and turn it into an entity. And later on, when more words like I love you goes in LUIS, it can identify the related intent easily.
However, in Chinese if I write:
我很喜歡你: which has the same meaning as in English above. Under LUIS it will be counted as 1 word. If I want to extract the word 喜歡 (which means "Love/Like"), I cannot do this in LUIS.
Only if I put space around 喜歡 like this: 我很 喜歡 你 will I be able to select 喜歡 as a particular entity.
My Question:
Are there any ways/methods/tricks that I can use so that, when someone enters joined-string, like what you see in the Chinese version, to LUIS, LUIS will be able to identify specific words as entity automatically, without any manual change?
Thank you very much in advance for all your help.
To perform machine learning, LUIS breaks an utterance into tokens based on culture. We cannot suppress tokenization. LUIS tokenizes Chinese at character level and returns tokenized entity whereas for English it tokenizes for every space or special character. In the zh-cn culture, LUIS expects the simplified Chinese character set instead of the traditional character set.
Hope this helps!!
In a part of my software I need, in different languages, lists of words having a fixed number of letters.
My software is already internationalized (using gettext, and it works fine). But, as it's not possible to translate a 4 letters word from english into a 4 letters word in another language (apart from some exceptions maybe), I can't imagine a reasonable way of letting gettext deal with these words lists.
So, for now, I decided to store my words like this (shortened example with english and french names):
FOUR_LETTERS_WORDS = { 'fr': ["ANGE", "ANIS", "ASIE", "AUBE", "AVEN", "AZUR"],
'en': ["LEFT", "LAMP", "ATOM", "GIRL", "PLUM", "NAVY", "GIFT", "DARK"] }
(This is python syntax, but the problem has not much to do with the programming language used)
The lists do not need to have the same length; they do not need to contain the same words.
My problem is following: if my software is to be translated in another language, like say, german, then all the strings that fall within the scope of gettext will be listed in the pot file and will be available for translation. But then, I also need a list of 4 letters words in german, that won't show up in the translation file.
I would like to know whether I need to think to ask the translator if he/she can also provide a list of such words, or if there's a better way to deal with this situation? (maybe finding a satisfying workaround with gettext?).
EDIT Realized the question has actually not much to do with the programming language, so removed the python* tags
You can do it with gettext. It's possible to use "keys" instead of complete sentences for translation.
If you use sentences in your .po files and don't want to have to translate the main language (let's say english), you don't need to translate them and only provide translation files for these words. If gettext finds a translation file, it uses it, else it will display the key (the msgid). It can be a complete sentence or a key, it does not matter.
To do that, you simply need to use a specific text domain for these words and use dgettext() function. The domain allows you to separate files depending on context, or whatever criteria of your choice (functionnality, sub-package, etc.).
To count these words, it's not as easy. You can count them with grep -c, for instance. You can provide a specific key that contains the number of 4 letters words (this would be a dirty hack on which you could probably not really rely).
Maybe there's another way in Python, I don't know this language...
I've recently discovered, to my astonishment (having never really thought about it before), machine-sorting Japanese proper nouns is apparently not possible.
I work on an application that must allow the user to select a hospital from a 3-menu interface. The first menu is Prefecture, the second is City Name, and the third is Hospital. Each menu should be sorted, as you might expect, so the user can find what they want in the menu.
Let me outline what I have found, as preamble to my question:
The expected sort order for Japanese words is based on their pronunciation. Kanji do not have an inherent order (there are tens of thousands of Kanji in use), but the Japanese phonetic syllabaries do have an order: あ、い、う、え、お、か、き、く、け、こ... and on for the fifty traditional distinct sounds (a few of which are obsolete in modern Japanese). This sort order is called 五十音順 (gojuu on jun , or '50-sound order').
Therefore, Kanji words should be sorted in the same order as they would be if they were written in hiragana. (You can represent any kanji word in phonetic hiragana in Japanese.)
The kicker: there is no canonical way to determine the pronunciation of a given word written in kanji. You never know. Some kanji have ten or more different pronunciations, depending on the word. Many common words are in the dictionary, and I could probably hack together a way to look them up from one of the free dictionary databases, but proper nouns (e.g. hospital names) are not in the dictionary.
So, in my application, I have a list of every prefecture, city, and hospital in Japan. In order to sort these lists, which is a requirement, I need a matching list of each of these names in phonetic form (kana).
I can't come up with anything other than paying somebody fluent in Japanese (I'm only so-so) to manually transcribe them. Before I do so though:
Is it possible that I am totally high on fire, and there actually is some way to do this sorting without creating my own mappings of kanji words to phonetic readings, that I have somehow overlooked?
Is there a publicly available mapping of prefecture/city names, from the government or something? That would reduce the manual mapping I'd need to do to only hospital names.
Does anybody have any other advice on how to approach this problem? Any programming language is fine--I'm working with Ruby on Rails but I would be delighted if I could just write a program that would take the kanji input (say 40,000 proper nouns) and then output the phonetic representations as data that I could import into my Rails app.
宜しくお願いします。
For Data, dig Google's Japanese IME (Mozc) data files here.
https://github.com/google/mozc/tree/master/src/data
There is lots of interesting data there, including IPA dictionaries.
Edit:
And you may also try Mecab, it can use IPA dictionary and can convert kanjis to katakana for most of the words
https://taku910.github.io/mecab/
and there is ruby bindings for that too.
https://taku910.github.io/mecab/bindings.html
and here is somebody tested, ruby with mecab with tagger -Oyomi
http://hirai2.blog129.fc2.com/blog-entry-4.html
just a quick followup to explain the eventual actual solution we used. Thanks to all who recommended mecab--this appears to have done the trick.
We have a mostly-Rails backend, but in our circumstance we didn't need to solve this problem on the backend. For user-entered data, e.g. creating new entities with Japanese names, we modified the UI to require the user to enter the phonetic yomigana in addition to the kanji name. Users seem accustomed to this. The problem was the large corpus of data that is built into the app--hospital, company, and place names, mainly.
So, what we did is:
We converted all the source data (a list of 4000 hospitals with name, address, etc) into .csv format (encoded as UTF-8, of course).
Then, for developer use, we wrote a ruby script that:
Uses mecab to translate the contents of that file into Japanese phonetic readings
(the precise command used was mecab -Oyomi -o seed_hospitals.converted.csv seed_hospitals.csv, which outputs a new file with the kanji replaced by the phonetic equivalent, expressed in full-width katakana).
Standardizes all yomikata into hiragana (because users tend to enter hiragana when manually entering yomikata, and hiragana and katakana sort differently). Ruby makes this easy once you find it: NKF.nkf("-h1 -w", katakana_str) # -h1 means to hiragana, -w means output utf8
Using the awesomely conveninent new Ruby 1.9.2 version of CSV, combine the input file with the mecab-translated file, so that the resulting file now has extra columns inserted, a la NAME, NAME_YOMIGANA, ADDRESS, ADDRESS_YOMIGANA, and so on.
Use the data from the resulting .csv file to seed our rails app with its built-in values.
From time to time the client updates the source data, so we will need to do this whenever that happens.
As far as I can tell, this output is good. My Japanese isn't good enough to be 100% sure, but a few of my Japanese coworkers skimmed it and said it looks all right. I put a slightly obfuscated sample of the converted addresses in this gist so that anybody who cared to read this far can see for themselves.
UPDATE: The results are in... it's pretty good, but not perfect. Still, it looks like it correctly phoneticized 95%+ of the quasi-random addresses in my list.
Many thanks to all who helped me!
Nice to hear people are working with Japanese.
I think you're spot on with your assessment of the problem difficulty. I just asked one of the Japanese guys in my lab, and the way to do it seems to be as you describe:
Take a list of Kanji
Infer (guess) the yomigana
Sort yomigana by gojuon.
The hard part is obviously step two. I have two guys in my lab: 高橋 and 高谷. Naturally, when sorting reports etc. by name they appear nowhere near each other.
EDIT
If you're fluent in Japanese, have a look here: http://mecab.sourceforge.net/
It's a pretty popular tool, so you should be able to find English documentation too (the man page for mecab has English info).
I'm not familiar with MeCab, but I think using MeCab is good idea.
Then, I'll introduce another method.
If your app is written in Microsoft VBA, you can call "GetPhonetic" function. It's easy to use.
see : http://msdn.microsoft.com/en-us/library/aa195745(v=office.11).aspx
Sorting prefectures by its pronunciation is not common. Most Japanese are used to prefectures sorted by 「都道府県コード」.
e.g. 01:北海道, 02:青森県, …, 13:東京都, …, 27:大阪府, …, 47:沖縄県
These codes are defined in "JIS X 0401" or "ISO-3166-2 JP".
see (Wikipedia Japanese) :
http://ja.wikipedia.org/wiki/%E5%85%A8%E5%9B%BD%E5%9C%B0%E6%96%B9%E5%85%AC%E5%85%B1%E5%9B%A3%E4%BD%93%E3%82%B3%E3%83%BC%E3%83%89
To make matter more specific:
How to detect people names (seems like simple case of named entity extraction?)
How to detect addresses: my best guess - find postcode (regexes); country and town names and take some text around them.
As for phones, emails - they could be probably caught by various regexes + preprocessing
Don't care about education/working experience at this point
Reasoning:
In order to build a fulltext index on resumes all vulnerable information should be stripped out from them.
P.S. any 3rd party APIs/services won't do as a solution.
The problem you're interested in is information extraction from semi structured sources. http://en.wikipedia.org/wiki/Information_extraction
I think you should download a couple of research papers in this area to get a sense of what can be done and what can't.
I feel it can't be done by a machine.
Every other resume will have a different format and layout.
The best you can do is to design an internal format and manually copy every resume content in there. Or ask candidates to fill out your form (not many will bother).
I think that the problem should be broken up into two search domains:
Finding information relating to proper names
Finding information that is formulaic
Firstly the information relating to proper names could probably be best found by searching for items that are either grammatically important or significant. I.e. English capitalizes only the first word of the sentence and proper nouns. For the gramatical rules you could look for all of the words that have the first letter of the word capitalized and check it against a database that contains the word and the type [i.e. Bob - Name, Elon - Place, England - Place].
Secondly: Information that is formulaic. This is more about the email addresses, phone numbers, and physical addresses. All of these have a specific formats that don't change. Use a regex and use an algorithm to detect the quality of the matches.
Watch out:
The grammatical rules change based on language. German capitalizes EVERY noun. It might be best to detect the language of the document prior to applying your rules. Also, another issue with this [and my resume sometimes] is how it is designed. If the resume was designed with something other than a text editor [designer tools] the text may not line up, or be in a bitmap format.
TL;DR Version: NLP techniques can help you a lot.
I am working on an application that allows users to input Japanese language characters. I am trying to come up with a way to determine whether the user's input is a Japanese kana (hiragana, katakana, or kanji).
There are certain fields in the application where entering Latin text would be inappropriate and I need a way to limit certain fields to kanji-only, or katakana-only, etc.
The project uses UTF-8 encoding. I don't expect to accept JIS or Shift-JIS input.
Ideas?
It sounds like you basically need to just check whether each Unicode character is within a particular range. The Unicode code charts should be a good starting point.
If you're using .NET, my MiscUtil library has some Unicode range support - it's primitive, but it should do the job. I don't have the source to hand right now, but will update this post with an example later if it would be helpful.
Not sure of a perfect answer, but there is a Unicode range for katakana and hiragana listed on Wikipedia. (Which I would expect are also available from unicode.org as well.)
Hiragana: Unicode: 3040-309F
Katakana: Unicode: 30A0–30FF
Checking those ranges against the input should work as a validation for hiragana or katakana for Unicode in a language-agnostic manner.
For kanji, I would expect it to be a little more complicated, as I
expect that the Chinese characters used in Chinese and Japanese are both included in the same range, but then again, I may be wrong here. (I can't expect that Simplified Chinese and Traditional Chinese to be included in the same range...)
oh oh! I had this one once... I had a regex with the hiragana, then katakana and then the kanji. I forget the exact codes, I'll go have a look.
regex is great because you double the problems. And I did it in PHP, my choice for extra strong auto problem generation
--edit--
$pattern = '/[^\wぁ-ゔァ-ヺー\x{4E00}-\x{9FAF}_\-]+/u';
I found this here, but it's not great... I'll keep looking
--edit--
I looked through my portable hard drive.... I thought I had kept that particular snippet from the last company... sorry.