Question classification of open-domain and fact-based questions Pipeline - TREC6

Description

Classify open-domain, fact-based questions into one of the following broad semantic categories: Abbreviation, Description, Entities, Human Beings, Locations or Numeric Values.

Live Demo Open in Colab Download

How to use

from sparknlp.pretrained import PretrainedPipeline 
pipeline = PretrainedPipeline("classifierdl_use_trec6_pipeline", lang = "en") 
import com.johnsnowlabs.nlp.pretrained.PretrainedPipeline
val pipeline = new PretrainedPipeline("classifierdl_use_trec6_pipeline", lang = "en")

Results

+------------------------------------------------------------------------------------------------+------------+
|document                                                                                        |class       |
+------------------------------------------------------------------------------------------------+------------+
|When did the construction of stone circles begin in the UK?                                     | NUM        |
+------------------------------------------------------------------------------------------------+------------+

Model Information

Model Name: classifierdl_use_trec6_pipeline
Type: pipeline
Compatibility: Spark NLP 2.7.1+
Edition: Official
Language: en