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markovian-nlp
Advanced tools
markovian-nlp
Quick start
As an isomorphic JavaScript package, there are multiple ways for clients, servers, and bundlers to start using this library. Several methods do not require installation.
RunKit
RunKit provides one of the least difficult ways to get started:
CodePen
Declare imports in the JS section to get started:
import {
ngramsDistribution,
sentences,
} from 'https://unpkg.com/markovian-nlp@latest?module';
const sentence = sentences('oh me, oh my');
console.log(sentence());
// example output: 'oh me oh me oh my'
Browsers
Insert the following element within the <head> tag of an HTML document:
<script src="https://unpkg.com/markovian-nlp@latest"></script>
After the script is loaded, the markovian browser global is exposed:
const sentence = markovian.sentences('oh me, oh my');
console.log(sentence());
// example output: 'oh me oh me oh my'
Node.js
With npm installed, run terminal command:
npm i markovian-nlp
Once installed, declare method imports at the top of each JavaScript file they will be used.
ES2015
Recommended
import {
ngramsDistribution,
sentences,
} from 'markovian-nlp';
CommonJS
const {
ngramsDistribution,
sentences,
} = require('markovian-nlp');
Usage
Markov text generation
Generate text sentences from a Markov process.
Potential applications: Natural language generation
In these examples, document is text from this source:
const document = 'That there is constant succession and flux of ideas in our minds...';
const oneSentence = sentences(document);
Generate a random sentence
By default, a nondeterministic sentence is generated without providing a seed:
oneSentence();
// output: 'i have observed in the chief yet we might be able by a one...'
oneSentence();
// output: 'this is not angry chiding or so easy to them from running away...'
Generate a repeatable sentence
Optionally providing a seed generates a deterministic sentence:
oneSentence(1);
// output: 'i would promote introduce a constant succession and hindering the path...'
oneSentence(1);
// output: 'i would promote introduce a constant succession and hindering the path...'
Generate multiple sentences
Optionally providing a seed generates deterministic sentences:
sentences({
document,
count: 3,
seed: 1,
});
// output: [
// 'i would promote introduce a constant succession and hindering the path...',
// 'he that train they seem to be glad to be done as may be avoided of our thoughts...',
// 'this wandering of attention and yet for ought i know this wandering thoughts i would promote...',
// ]
View n-grams distribution
View the n-grams distribution of text.
Potential applications: Markov models
ngramsDistribution('birds have featured in culture and art since prehistoric times');
// output: {
// and: { _end: 0, _start: 0, art: 1 },
// art: { _end: 0, _start: 0, since: 1 },
// birds: { _end: 0, _start: 1, have: 1 },
// culture: { _end: 0, _start: 0, and: 1 },
// featured: { _end: 0, _start: 0, in: 1 },
// have: { _end: 0, _start: 0, featured: 1 },
// in: { _end: 0, _start: 0, culture: 1 },
// prehistoric: { _end: 0, _start: 0, times: 1 },
// since: { _end: 0, _start: 0, prehistoric: 1 },
// times: { _end: 1, _start: 0 },
// }
Each number represents the sum of occurrences.
| startgram | endgram | bigrams |
|---|---|---|
| "birds" | "times" | all remaining keys ("have featured", "featured in", etc.) |
API
ngramsDistribution(document)
Input
| user-defined parameter | type | implements | intermediate transformations |
|---|---|---|---|
document | String | compromise(document) | normalization, rule-based text parsing |
Return value
| type | description |
|---|---|
| Object | distributions of unigrams to startgrams, endgrams, and following bigrams |
// pseudocode signature representation (does not run)
ngramsDistribution(document) => ({
...unigrams: {
...{ ...bigram: bigramsDistribution },
_end: endgramsDistribution,
_start: startgramsDistribution,
},
});
sentences(document)(seed)
sentences({ document[, count][, seed] })
Input
| user-defined parameter | type | optional | default value | implements | description |
|---|---|---|---|---|---|
document, options.document | String | false | compromise(document) | Text. | |
seed, options.seed | Number | true | undefined | Chance(seed) | Leave undefined (default) for nondeterministic results, or specify seed for deterministic results. |
options | Object | true | |||
options.count | Number | true | 1 | Number of sentences to output. |
Return value
| type | description |
|---|---|
| Array[Strings...] | generated sentences |
Glossary
Learn more about computational linguistics and natural language processing (NLP) on Wikipedia.
The following terms are used in the API documentation:
| term | description |
|---|---|
| bigram | 2-gram sequence |
| deterministic | repeatable, non-random |
| endgram | final gram in a sequence |
| n-gram | contiguous gram (word) sequence |
| startgram | first gram in a sequence |
| unigram | 1-gram sequence |
Keywords
FAQs
NLP tools generate Markov sentences & models.
The npm package markovian-nlp receives a total of 3 weekly downloads. As such, markovian-nlp popularity was classified as not popular.
We found that markovian-nlp demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
Package last updated on 12 Oct 2018
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