CoreNLP vs Sentence Transformers
Overview
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CLI (Node.js)
Manual
Detailed Comparison
It provides a set of natural language analysis tools written in Java. It can take raw human language text input and give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize and interpret dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases or word dependencies, and indicate which noun phrases refer to the same entities. | It provides an easy method to compute dense vector representations for sentences, paragraphs, and images. The models are based on transformer networks like BERT / RoBERTa / XLM-RoBERTa etc. and achieve state-of-the-art performance in various tasks. |
An integrated NLP toolkit with a broad range of grammatical analysis tools;
A fast, robust annotator for arbitrary texts, widely used in production;
A modern, regularly updated package, with the overall highest quality text analytics;
Support for a number of major (human) languages;
Available APIs for most major modern programming languages
Ability to run as a simple web service | Vector representations for sentences, paragraphs, and images;
Based on transformer networks like BERT / RoBERTa / XLM-RoBERTa |
Statistics | |
GitHub Stars 10.0K | GitHub Stars - |
GitHub Forks 2.7K | GitHub Forks - |
Stacks 19 | Stacks 63 |
Followers 23 | Followers 3 |
Votes 1 | Votes 1 |
Integrations | |
What are some alternatives to CoreNLP, Sentence Transformers?
rasa NLU
rasa NLU (Natural Language Understanding) is a tool for intent classification and entity extraction. You can think of rasa NLU as a set of high level APIs for building your own language parser using existing NLP and ML libraries.
SpaCy
It is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products. It comes with pre-trained statistical models and word vectors, and currently supports tokenization for 49+ languages.
Speechly
It can be used to complement any regular touch user interface with a real time voice user interface. It offers real time feedback for faster and more intuitive experience that enables end user to recover from possible errors quickly and with no interruptions.
MonkeyLearn
Turn emails, tweets, surveys or any text into actionable data. Automate business workflows and saveExtract and classify information from text. Integrate with your App within minutes. Get started for free.
Jina
It is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
FastText
It is an open-source, free, lightweight library that allows users to learn text representations and text classifiers. It works on standard, generic hardware. Models can later be reduced in size to even fit on mobile devices.
Flair
Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), part-of-speech tagging (PoS), sense disambiguation and classification.
Social Verdict
Track how your brand is talked about on Reddit - every mention, every post, every trend. Real-time monitoring and sentiment analysis.
HappyInsights — Turn feedback into valuable insights
HappyInsights is an AI-powered comment intelligence platform that helps YouTube creators get a clear handle on audience sentiment and lift engagement without getting bogged down in hours of manual analysis.
BrandNata
BrandNata is an enterprise-grade AI platform that revolutionizes brand management by consolidating campaign data from 200+ entities across Instagram, Facebook, LinkedIn, YouTube, Reddit, and more. Track real-time performance, sentiment, budget allocation, and ROI with unified dashboards that deliver actionable insights for marketing leaders.
