This is an automated email from the ASF dual-hosted git repository. aradzinski pushed a commit to branch NLPCRAFT-518 in repository https://gitbox.apache.org/repos/asf/incubator-nlpcraft.git
commit 6fd7e8f3fcb70c2e9bc269b1d1c95e43fdc27d34 Author: Aaron Radzinski <[email protected]> AuthorDate: Mon Oct 17 13:18:44 2022 -0700 Update CalculatorModel.scala --- .../org/apache/nlpcraft/examples/time/CalculatorModel.scala | 11 +++++------ 1 file changed, 5 insertions(+), 6 deletions(-) diff --git a/nlpcraft-examples/calculator/src/main/scala/org/apache/nlpcraft/examples/time/CalculatorModel.scala b/nlpcraft-examples/calculator/src/main/scala/org/apache/nlpcraft/examples/time/CalculatorModel.scala index 49268abf..2d95c360 100644 --- a/nlpcraft-examples/calculator/src/main/scala/org/apache/nlpcraft/examples/time/CalculatorModel.scala +++ b/nlpcraft-examples/calculator/src/main/scala/org/apache/nlpcraft/examples/time/CalculatorModel.scala @@ -29,7 +29,6 @@ import java.util.Properties */ object CalculatorModel: private val OPS: Map[String, (Int, Int) => Int] = Map("+" -> (_ + _), "-" -> (_ - _), "*" -> (_ * _), "/" -> (_ / _)) - private val PIPELINE: NCPipeline = val props = new Properties() props.setProperty("annotators", "tokenize, ssplit, pos, lemma, ner") @@ -58,9 +57,9 @@ class CalculatorModel extends NCModelAdapter(NCModelConfig("nlpcraft.calculator. @NCIntent( "intent=calc options={ 'ordered': true }" + - " term(x)={# == 'stanford:number'} " + - " term(op)={# == 'nlp:token' && has(list('+', '-', '*', '/'), meta_ent('nlp:token:text')) == true} " + - " term(y)={# == 'stanford:number'}" + " term(x)={# == 'stanford:number'}" + + " term(op)={has(list('+', '-', '*', '/'), meta_ent('nlp:token:text')) == true}" + + " term(y)={# == 'stanford:number'}" ) def onMatch( ctx: NCContext, @@ -72,8 +71,8 @@ class CalculatorModel extends NCModelAdapter(NCModelConfig("nlpcraft.calculator. @NCIntent( "intent=calcMem options={ 'ordered': true }" + - " term(op)={# == 'nlp:token' && has(list('+', '-', '*', '/'), meta_ent('nlp:token:text')) == true} " + - " term(y)={# == 'stanford:number'}" + " term(op)={has(list('+', '-', '*', '/'), meta_ent('nlp:token:text')) == true}" + + " term(y)={# == 'stanford:number'}" ) def onMatchMem( ctx: NCContext,
