Stanford CoreNLP

What do you like best about Stanford CoreNLP?

The Stanford Parser is an easy introduction to natural language processing (NLP). The program uses a combination of approaches to identify and tag both the individual components (syntax) within a sentence and to accurately assign the relationship between the words (semantics). Users can download the Java based version of the program, or experiment with it on their website.

What do you dislike about Stanford CoreNLP?

The Stanford Parser is one of many natural language parsers available on the market. I prefer Stanford for its ease and accessibility. The use of a recurrent neural network may produce greater results for someone working in a highly technical and linguistically complex environment, where immediacy and accuracy are equally weighted.

What problems is Stanford CoreNLP solving and how is that benefiting you?

Developing an interactive knowledge base that exceeds the limits of a preset FAQ is essential for customer engagement. The Stanford Parser provides the foundation for generating the framework for that interaction.

What do you like best about Stanford CoreNLP?

The Stanford Parser is a natural Language parser that doesn't require a ivy league degree to use; plus it is free; which is a huge plus; I use it surprising more than you would think, as i am currently trying to use it to feed langue into a Machine Learning Data Structure; with the ultimate goal of creating a better chat bot

What do you dislike about Stanford CoreNLP?

Although built on solid foundations; the User Interface is very 1990's / Early 2000's; If the GUI was re-designed or even updated to modern standards, i feel it would benefit greatly.

Recommendations to others considering Stanford CoreNLP:

Just use it; its free to use and it helps immensely just to jump right in and being playing around with it; this will get you accumulated to what the program can do, as well as what you can apply it to in your business. I would say that even if you don't think you need a program like this; download it; or use the web interface; and try it. You might be surprised to see its application is vast and extremely useful.

What problems is Stanford CoreNLP solving and how is that benefiting you?

Building algorithms, Machine Learning or otherwise, is extremely complex; Stanford made this resource available to all which is great, We are able to use this program in a surprising amount of ways; from your typical neural network / learning algorithms; to speech analysis and even analyzing your own emails or proposals before sending out to clients to create a more efficient response.

What do you like best about Stanford CoreNLP?

The amount of options that Stanford NER provides means you'll never go anywhere else for any kind of NER tasks

What do you dislike about Stanford CoreNLP?

The lack of good support of non-English languages

Recommendations to others considering Stanford CoreNLP:

Get started with the online demo to determine whether it's for you

What problems is Stanford CoreNLP solving and how is that benefiting you?

We've used Stanford NER to mine and tag incoming textual data to generate media rich representations of the input. This has led to a more sophisticated interface and taken us one step closer to making our platform smart

What do you like best about Stanford CoreNLP?

Ease of use and implementation and works effectively in most cases. Open source license and straightforward algorithm.

What do you dislike about Stanford CoreNLP?

There are more powerful tools out there like spaCy which use deep learning techniques to identify more information like context in a sentence.

What problems is Stanford CoreNLP solving and how is that benefiting you?

Tokenize OCR data to pre-process and pass to machine learning models. Works fast and is accurate for real time applications.

What do you like best about Stanford CoreNLP?

it's an open source and very easy to use this library in java , it splits the sentence and gives the words(entity) as a result which actually makes sense like person,location etc , for using it into the java,

1) we need to import edu.stanford.nlp.* and then

2) we have to set all the properties which we want to list.

3) then we have to create text document and pass it to the StanfordCoreNLP's annote () method.

and you'll get all the Entities present in your text or document

What do you dislike about Stanford CoreNLP?

this project is evolving right now so it's not true that you'll get accurate result for every scenario all the time!!

Recommendations to others considering Stanford CoreNLP:

It's highly trained and very easy to use and little bit less accurate Named Entity recognition API for java.

What problems is Stanford CoreNLP solving and how is that benefiting you?

we use it for Spam email classification on the emails which are being sent on our companies helpline email id and we need to process 10 to 20 emails every minute!!