wink-nlp - npm Package Compare versions

Comparing version 1.8.0 to 1.8.1

.nyc_output/processinfo/index.json

@@ -1,1 +0,1 @@
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CHANGELOG.md

@@ -0,1 +1,7 @@
+# [Operational update](https://github.com/winkjs/wink-nlp/releases/tag/1.8.1)
+## Version 1.8.1 September 22, 2021
+
+### ⚙️ Updates
+- Included NLP Pipe details in the README file. 🤓
+
 # [Introducing Typescript support](https://github.com/winkjs/wink-nlp/releases/tag/1.8.0)
@@ -2,0 +8,0 @@ ## Version 1.8.0 July 31, 2021

package.json

 {
   "name": "wink-nlp",
-  "version": "1.8.0",
+  "version": "1.8.1",
   "description": "Developer friendly NLP ✨",
@@ -5,0 +5,0 @@ "keywords": [

README.md

@@ -14,2 +14,9 @@ # winkNLP
 ## Features
+WinkNLP has a comprehensive processing pipeline covering tokenization, sentence boundary detection (sbd), negation handling, sentiment analysis, part-of-speech (pos) tagging, named entity recognition (ner), custom entities recognition (cer):
+
+<img src="https://winkjs.org/images/wink-nlp-processing-pipeline.png" alt="Processing pipeline: text, tokenization, SBD, negation, sentiment, NER, POS, CER" title="WinkNLP processing pipeline">
+
+At every stage a range of properties become accessible for tokens, sentences, and entities. Read more about the processing pipeline and how to configure it in the [winkNLP documentation](https://winkjs.org/wink-nlp/processing-pipeline.html).
+
+
 It packs a rich feature set into a small foot print codebase of [under 1500 lines](https://coveralls.io/github/winkjs/wink-nlp?branch=master):
@@ -23,21 +30,19 @@
 
-4. Easy information extraction from raw text
+4. Extensive [text processing features](https://winkjs.org/wink-nlp/its-as-helper.html) such as bag-of-words, frequency table, stop word removal, readability statistics computation and many more.
 
-5. Extensive [text processing features](https://winkjs.org/wink-nlp/its-as-helper.html) such as bag-of-words, frequency table, stop word removal, readability statistics computation and many more.
+5. Pre-trained [language models](https://winkjs.org/wink-nlp/language-models.html) with sizes starting from <3MB onwards
 
-6. Pre-trained [language models](https://winkjs.org/wink-nlp/language-models.html) with sizes starting from <3MB onwards
+6. [BM25-based vectorizer](https://winkjs.org/wink-nlp/bm25-vectorizer.html)
 
-7. [BM25-based vectorizer](https://winkjs.org/wink-nlp/bm25-vectorizer.html)
+7. Multiple [similarity](https://winkjs.org/wink-nlp/similarity.html) methods
 
-8. Multiple [similarity](https://winkjs.org/wink-nlp/similarity.html) methods
+8. Word vector integration
 
-9. Word vector integration
+9. No external dependencies
 
-10. Comprehensive [NLP pipeline](https://winkjs.org/wink-nlp/processing-pipeline.html) covering tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech (pos) tagging, lemmatization, named entity extraction, custom entities detection and pattern matching
+10. [Runs on web browsers](https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html)
 
-11. No external dependencies
+11. [Typescript support](https://github.com/winkjs/wink-nlp/blob/master/types/index.d.ts).
 
-12. [Runs on web browsers](https://winkjs.org/wink-nlp/wink-nlp-in-browsers.html).
 
-
 ## Installation
@@ -113,3 +118,2 @@
 
-
 ## Speed & Accuracy
@@ -116,0 +120,0 @@ The [winkNLP](https://winkjs.org/wink-nlp/) processes raw text at **~525,000 tokens per second** with its default language model — [wink-eng-lite-model](https://github.com/winkjs/wink-eng-lite-model), when [benchmarked](https://github.com/bestiejs/benchmark.js) using "Ch 13 of Ulysses by James Joyce" on a 2.2 GHz Intel Core i7 machine with 16GB RAM. The processing included the entire NLP pipeline — tokenization, sentence boundary detection, negation handling, sentiment analysis, part-of-speech tagging, and named entity extraction. This speed is way ahead of the prevailing speed benchmarks.

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Total package byte prevSize

543243

increased by0.11%

Number of lines in readme file

154

increased by2.67%

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