New models: Product Sentiment Analysis & Text Extractors

New models: Product Sentiment Analysis & Text Extractors

We are excited to announce some new cool public models for MonkeyLearn: product sentiment analysis, keywords extraction and entity extraction including person, company and location. These models are pre-trained by the MonkeyLearn team and ready to use models through our integrations or our API.

You can try these public models by login on your MonkeyLearn account and then going to explore.

Product Sentiment Analysis

Description

This model classifies product reviews and opinions in English as positive or negative according to the sentiment.

Try the product sentiment analysis classifier here.

Example

Input:

"Horrible camera! VERY cheap camera body, for starters. Very poor focus on a still subject. If the subject so much as twitches or blinks,you have a blurry shot. Colors aren't even close to being true, white balance is way off, and noise is high in a natural light setting. While I didn't expect my shots to be the same as my Canon DSLR, I did expect to get snapshot quality shots. It will be returning to Amazon first  thing Monday morning. Very disappointing, to say the least."

Output:

Tag: Negative Confidence: 96.5%

Keyword Extraction

Description

Extract keywords from text in English. Keywords can be compounded by one or more words and are defined as the important topics in your content and can be used to index data, generate tag clouds or for searching.

Try the keyword extractor here.

Example

Input:

"Elon Musk has shared a photo of the spacesuit designed by SpaceX. This is the second image shared of the new design and the first to feature the spacesuit’s full-body look."

Output:

Keywords: spacesuit, Elon Musk, full-body look, second image, new design, photo, SpaceX

Peron Extractor

Description

This pre-trained model is used to extract person names from text.

Try the person extractor here.

Example

Input:

"SpaceX is an aerospace manufacturer and space transport services company headquartered in California. It was founded in 2002 by entrepreneur and investor Elon Musk with the goal of reducing space transportation costs and enabling the colonization of Mars."

Output:

Person: Elon Musk

Company Extractor

Description

Extract company and organization entities from text.

Try the company extractor here.

Example

Input:

"SpaceX is an aerospace manufacturer and space transport services company headquartered in California. It was founded in 2002 by entrepreneur and investor Elon Musk with the goal of reducing space transportation costs and enabling the colonization of Mars."

Output:

Company: SpaceX

Location Extractor

Description

This pre-trained model is used to extract locations from text.

Try the location extractor here.

Example

Input:

"SpaceX is an aerospace manufacturer and space transport services company headquartered in California. It was founded in 2002 by entrepreneur and investor Elon Musk with the goal of reducing space transportation costs and enabling the colonization of Mars."

Output:

Location: California, Mars.

Share your thoughts

If you have any questions, comments or feedback about these new models, please email us to hello@monkeylearn.com or comment on this post.

Chat soon, take care!

Federico Pascual

March 26th, 2015

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