Natural Language Processing with Ruby
summary
Describes a working pipeline that actually loads pre-trained OpenNLP models and uses JRuby and OpenNLP interop to do sentence segmentation, tokenization, POS tagging, named-entity recognition and Porter stemming. Packages arrive as three gems (wrapper plus English and German models), a composable-operations pipeline gem, and a prototype keyword-extractor on GitHub that builds a co‑occurrence graph and runs TextRank to return, for example, the top 10 key phrases; the prototype runs but is not production hardened.
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chapters (12)
- 0:00Start
- 0:10Natural Language Processing (NLP) with JRuby and OpenNLP
- 2:53Examples
- 9:27Segmentation
- 9:44Sentence Detection
- 10:59Tokenization
- 12:15Part-of-Speech Tagging
- 13:13Stemming
- 14:22Named Entity Recognition
- 17:00Composable Operations
- 18:17Pre-Processing Pipeline
- 23:21Keyword Extraction Pipeline
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