Nit wrapper for Stanford CoreNLP

Stanford CoreNLP provides a set of natural language analysis tools which can take raw text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, and mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, etc.

This wrapper needs the Stanford CoreNLP jars that run on Java 1.8+.

See http://nlp.stanford.edu/software/corenlp.shtml.

NLPProcessor

Java client

var proc = new NLPProcessor("path/to/StanfordCoreNLP/jars")

var doc = proc.process("String to analyze")

for sentence in doc.sentences do
    for token in sentence.tokens do
        print "{token.lemma}: {token.pos}"
    end
end

NLPServer

The NLPServer provides a wrapper around the StanfordCoreNLPServer.

See https://stanfordnlp.github.io/CoreNLP/corenlp-server.html.

var cp = "/path/to/StanfordCoreNLP/jars"
var srv = new NLPServer(cp, 9000)
srv.start

NLPClient

The NLPClient is used as a NLPProcessor with a NLPServer backend.

var cli = new NLPClient("http://localhost:9000")
var doc = cli.process("String to analyze")

NLPIndex

NLPIndex extends the StringIndex to use a NLPProcessor to tokenize, lemmatize and tag the terms of a document.

var index = new NLPIndex(proc)

var d1 = index.index_string("Doc 1", "/uri/1", "this is a sample")
var d2 = index.index_string("Doc 2", "/uri/2", "this and this is another example")
assert index.documents.length == 2

matches = index.match_string("this sample")
assert matches.first.document == d1

TODO

• Use JWrapper
• Use options to choose CoreNLP analyzers
• Analyze sentences dependencies
• Analyze sentiment