DKPro Core is a collection of software components for natural language processing (NLP) based on the Apache UIMA framework. Many powerful and state-of-the-art NLP components are already freely available in the NLP research community. New and improved components are being developed and released continuously. The components cover the whole range of NLP-related processing tasks. DKPro Core provides wrappers for such third-party tool as well as original NLP components. DKPro Core builds heavily on uimaFIT which allows for rapid and easy development of NLP processing pipelines.
Apache OpenNLP is a machine learning based toolkit for the processing of natural language text. It supports the most common NLP tasks, such as tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing, and coreference resolution. These tasks are usually required to build more advanced text processing services.
The AlchemyAPI Android SDK enables real-time semantic analysis of text, HTML, or Internet-hosted Web page content. The SDK provides mechanisms to extract Concepts, Named Entities, Keywords and Tags, Categories, and clean HTML into text, and even detects languages. It can analyze text in eight different languages: English, French, German, Italian, Portuguese, Russian, Spanish, and Swedish. Example code and a demo application are included to help get you started.
DKPro WSD provides UIMA components which encapsulate corpus readers, linguistic annotators, lexical semantic resources, WSD algorithms, and evaluation and reporting tools. You configure the components, or write new ones, and arrange them into a data processing pipeline. DKPro WSD is modular and flexible. Components which provide the same functionality can be freely swapped. You can easily run the same algorithm on different data sets, or test several different algorithms on the same data set.
The Language Detection Library for Java is a Java library to detect the natural languages in which texts are written. This task is also known as "language identification", "language guessing", and "language recognition". It has over 99% precision for more than 40 languages. The supported languages are Afrikaans, Arabic, Bulgarian, Bengali, Czech, German, Greek, English, Spanish, Persian, Finnish, French, Gujarati, Hebrew, Hindi, Croatian, Hungarian, Indonesian, Italian, Japanese, Kannada, Korean, Macedonian, Malayalam, Marathi, Nepali, Dutch, Punjabi, Polish, Portuguese, Romanian, Russian, Slovak, Somali, Albanian, Swedish, Swahili, Tamil, Telugu, Thai, Tagalog, Turkish, Ukrainian, Urdu, Vietnamese, and Simplified/Traditional Chinese.
foma is a compiler, programming language, and C library for constructing finite-state automata and transducers for various uses. It has specific support for many natural language processing applications such as producing morphological analyzers. Although NLP applications are probably the main use of foma, it is sufficiently generic to use for a large number of purposes. It comes with an xfst-compatible interface and regular expression language. The library contains efficient implementations of all classical automata/transducer algorithms: determinization, minimization, epsilon-removal, composition, and boolean operations. More advanced construction methods are also available: context restriction, quotients, first-order regular logic, transducers from replacement rules, etc.