Examples with Span jcog.io.Twokenize.Span used on opensource projects

Example 1 with Span

use of jcog.io.Twokenize.Span in project narchy by automenta.

the class Twenglish method parseSentence.

@NotNull
protected Collection<TaskBuilder> parseSentence(String source, @NotNull NAR n, @NotNull List<Span> s) {
    LinkedList<Term> t = new LinkedList();
    Span last = null;
    for (Span c : s) {
        t.add(spanToTerm(c));
        last = c;
    }
    if (t.isEmpty())
        return Collections.emptyList();
    // Atomic sentenceType = FRAGMENT;
    // if ((last!=null) && ("punct".equals(last.pattern))) {
    // switch (last.content) {
    // case ".": sentenceType = JUDGMENT; break;
    // case "?": sentenceType = QUESTION; break;
    // //case "@": sentenceType = QUEST; break;
    // case "!": sentenceType = GOAL; break;
    // }
    // }
    // if (!"words".equals(sentenceType.toString()))
    // t.removeLast(); //remove the punctuation, it will be redundant
    List<TaskBuilder> tt = new ArrayList();
    // 1. add the logical structure of the sequence of terms
    if (inputProduct) {
        Term tokens = $.p(t.toArray(new Term[t.size()]));
        // Term q =
        // $.image(2,
        // $.the(source),
        // sentenceType,
        // tokens
        // )
        Term q = $.func("hear", Atomic.the(source), tokens);
        // n.task(q + ". %0.95|0.95%");
        TaskBuilder newtask = new TaskBuilder(q, BELIEF, 1f, n).present(n);
        // TODO non-string construct
        tt.add(newtask);
    }
    return tt;
}

Example 2 with Span

use of jcog.io.Twokenize.Span in project narchy by automenta.

the class Twenglish method parse.

/**
 * returns a list of all tasks that it was able to parse for the input
 */
@NotNull
public List<TaskBuilder> parse(String source, @NotNull NAR n, String s) {
    List<TaskBuilder> results = $.newArrayList();
    List<Span> tokens = Twokenize.twokenize(s);
    List<List<Span>> sentences = $.newArrayList();
    List<Span> currentSentence = $.newArrayList(tokens.size());
    for (Span p : tokens) {
        currentSentence.add(p);
        if ("punct".equals(p.pattern)) {
            switch(p.content) {
                case ".":
                case "?":
                case "!":
                    if (!currentSentence.isEmpty()) {
                        sentences.add(currentSentence);
                        currentSentence = $.newArrayList();
                        break;
                    }
            }
        }
    }
    if (!currentSentence.isEmpty())
        sentences.add(currentSentence);
    for (List<Span> x : sentences) {
        Collection<TaskBuilder> ss = parseSentence(source, n, x);
        if (ss != null)
            results.addAll(ss);
    }
    if (!results.isEmpty()) {
    // if (!languageBooted) {
    // 
    // 
    // results.add(0, n.task(new StringBuilder(
    // "<{word,pronoun,qpronoun,prepos,conjunc} -]- symbol>.").toString()));
    // results.add(0, n.task(new StringBuilder(
    // "$0.90;0.90$ <(*,<$a-->[$d]>,<is-->[verb]>,<$b-->[$d]>) =/> <$a <-> $b>>.").toString()));
    // 
    // languageBooted = true;
    // }
    }
    return results;
}