biangbiang
v0.1.6
Published
This package provides methods for Chinese language analysis and exploration in Node.js. In particular, it provides three broad functions:
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biangbiang
This package provides methods for Chinese language analysis and exploration in Node.js. In particular, it provides three broad functions:
- Dictionary definitions of words
- Retrieval and calculation of character and word frequency statistics
- Hierarchical decomposition of characters into components
Installation
For npm:
npm install biangbiang
For Yarn:
yarn add biangbiang
Getting started
With import
:
import biangbiang from "biangbiang";
With require
:
var biangbiang = require('biangbiang');
Methods
Dictionary
define(word, dictionary)
Get the pinyin and definition of a word, where dictionary is "simplified", "traditional", or "merged". Also returns the frequency index (rank).
define('面条', 'simplified');
{
simplified: '面条',
traditional: '麵條',
pinyin: 'mian4 tiao2',
definition: 'noodles',
index: 6029
}
kind(character)
Check if a character is a traditional or simplified one. If so, returns the other form. type
is 1
for simplified, 2
for traditional, and 3
for both.
kind("面");
{ type: 1, other: '麵'}
wordsContaining(character)
Get a list of all dictionary words containing a character, sorted in order of decreasing frequency.
wordsContaining('面');
[
{
word: '面',
index: 322,
},
{
word: '里面',
index: 706,
},
{
word: '面对',
index: 930,
},
{
word: '外面',
index: 1234,
},
{
word: '后面',
index: 1270,
},
...
]
Frequency
characterFrequency(character)
Get frequency statistics for a character.
characterFrequency('面');
{
symbol: '面',
index: 211,
frequency: 1631866,
percentage: 0.0006532897206780486,
cumulativePercentage: 0.7101332080329651,
}
wordFrequency(word)
Get frequency statistics for a word.
wordFrequency('面条');
{
symbol: '面条',
index: 6029,
frequency: 66879,
percentage: 0.000015823013308250793,
cumulativePercentage: 0.8864603725508198,
}
multiFrequency(sentence)
Get frequency statistics for a body of text.
multiFrequency('我喜欢吃面条。');
{
byCharacter: [
{
symbol: '我',
index: 1,
frequency: 107133693,
percentage: 0.042889146765223256,
cumulativePercentage: 0.12608816399204145,
},
{
symbol: '喜',
index: 479,
frequency: 681772,
percentage: 0.0002729357921827617,
cumulativePercentage: 0.8216732504061582,
},
{
symbol: '欢',
index: 1490,
frequency: 140530,
percentage: 0.000056258788679270345,
cumulativePercentage: 0.9496496712024702,
},
{
symbol: '吃',
index: 42,
frequency: 9348265,
percentage: 0.0037424184526636244,
cumulativePercentage: 0.46991986609112824,
},
{
symbol: '面',
index: 211,
frequency: 1631866,
percentage: 0.0006532897206780486,
cumulativePercentage: 0.7101332080329651,
},
{
symbol: '条',
index: 169,
frequency: 2102653,
percentage: 0.0008417612665824651,
cumulativePercentage: 0.6785621013285376,
},
{
symbol: '。',
index: -1,
frequency: -1,
percentage: -1,
cumulativePercentage: -1,
},
],
indices: [1, 479, 1490, 42, 211, 169],
percentages: [
0.042889146765223256,
0.0002729357921827617,
0.000056258788679270345,
0.0037424184526636244,
0.0006532897206780486,
0.0008417612665824651,
],
cumulativePercentages: [
0.12608816399204145,
0.8216732504061582,
0.9496496712024702,
0.46991986609112824,
0.7101332080329651,
0.6785621013285376,
],
}
Components
decompose(character, depth)
Decompose a character into its components up to a specified depth. If depth is undefined, then the full component tree is returned.
decompose('面');
{
丆: {
'㇐': '㇐',
'㇓': '㇓',
},
囬: {
'55103': {
'10001': {
'10001': '㇑',
},
二: {
二: '㇐',
},
},
囗: {
'⺆': {
'㇑': '㇑',
'㇆': '㇆',
},
'㇐': '㇐',
},
},
}
charactersWithComponent(component)
Get a list of characters containing a component, sorted in order of decreasing frequency.
charactersWithComponent('囗');
[
{ character: '回', index: 139 },
{ character: '图', index: 166 },
{ character: '口', index: 307 },
{ character: '因', index: 381 },
{ character: '西', index: 382 },
{ character: '团', index: 388 },
{ character: '困', index: 413 },
{ character: '国', index: 544 },
{ character: '围', index: 644 },
{ character: '圈', index: 717 },
...
]
How it works
JSON files containing character/word/component information are generated by /src/prepare.js from raw files contained in /data/raw, with outputs saved to /data/processed.
The preparation script can also be run with npm run prepare
or yarn prepare
.
Sources
- Dictionary entries are entirely from CEDICT
- Frequency statistics are from BCC_LEX_Zh
- Character composition entries are from CJK-decomp
This project was inspired by HanziJS and offers many of the same functionalities.
Etymology
Biangbiang noodles are a common cuisine in China's Shaanxi province. The character for 'biáng' is one of the most complicated in modern usage. Ironically, is not (yet) included in any of our datasets, as the character was only added to Unicode in March of 2020.