Building with Watson - Interpreting Language Using the Natural Language Classifier API

Building an App Using the Natural Language Classifier

#BuildingWithWatson

Housekeeping Items

• Webinar slides, live recording and Q&A will be emailed

• Ask questions at any time during the presentation - Use chat window on the webinar panel - We're on Twitter: @IBMWatson #BuildingWithWatson

© 2015 International Business Machines Corporation

#BuildingWithWatson

Our Expert: Rahul A. Garg


Strategy and Offering Management, Watson Solutions

#BuildingWithWatson

What will be covered today?

• Overview• Sample Calls• Parameters• Q&A


#BuildingWithWatson

Overview• Watson Natural Language Classifier interprets

and classifies natural language with confidence.

• NLC is tuned and tailored to short text (1000 characters or less) and can be trained to function in any domain or application.

• Variety of uses such as Q&A


#BuildingWithWatson

Usage Examples

• Tackle common questions • Classify SMS texts • Classify tweets


#BuildingWithWatson© 2015 International Business Machines Corporation

#BuildingWithWatson

Sample Application: Questions on the NLC

• This application shows how to build a question-and-answer application


#BuildingWithWatson

Preparing Data• Train the NLC using data in comma-separated value (CSV) format.• Rows vs. Columns - Row: Example record - Columns: Based on the number of records; contains representative text to

classify and classes that apply to the text


CSV file with four records. Each record in this sample includes the text input and one class, which are separated

by a comma.

#BuildingWithWatson

Creating and Training Classifier• $ curl -i -u "<username>":"<password>" \• -F training_data=@<path_to_file>/weather_data_train.csv \• -F training_metadata= "{\"language\":\"en\",\"name\”

:\"TutorialClassifier\"}" \"https://gateway.watsonplatform.net/natural-language-classifier/api/v1/classifiers"

• Reference


#BuildingWithWatson

Sample Response• { • "name": "TutorialClassifier", • "language": "en", • "status": "Training", • "url": "https://gateway.watsonplatform.net/natural-language-

classifier/api/v1/classifiers/10D41B-nlc-1", • "classifier_id": "10D41B-nlc-1", • "created": "2015-05-28T18:01:57.393Z", • "status_description": "The classifier instance is in its training phase, not yet

ready to accept classify requests" • }


#BuildingWithWatson

Classifying Text• $ curl -G -u "<username>":"<password>" \

"https://gateway.watsonplatform.net/natural-language-classifier/api/v1/classifiers/<classifier_id>/classify" \ --data-urlencode "text=How hot will it be today?"


#BuildingWithWatson

Sample Response• {• "classifier_id": "10D41B-nlc-1", • "url": "https://gateway.watsonplatform.net/natural-language-

classifier/api/v1", • "text": "How hot will it be today?", • "top_class": "temperature", • "classes": [ • { "class_name": "temperature", "confidence": 0.9998201258549781 }, • { "class_name": "conditions", "confidence": 0.00017987414502176904 }

] }


#BuildingWithWatson

Are you ready to get started?

• Watson App Gallery• Getting Started Docs• Toolkit for NLC• API Explorer• API Reference Guide



Q&A


What’s next?• Look out for a follow up email with a link to the on-demand version of the webinar,

presentation slides and Q&A recap

• The series continues bi-weekly on Wednesdays @ 12pm ET / 9am PT

• Wednesday, December 2, 2015 • Optimize Conflicting Decisions with the Tradeoff Analytics API


Thank you for attending!

Contact usPhone: 1-877-253-0308

Email: [email protected]: Watson Developer Cloud

Technology

Building with Watson - Interpreting Language Using the Natural Language Classifier API