CoreNLP

Introduction to Stanford CoreNLP

Stanford CoreNLP is a comprehensive suite of natural language processing (NLP) tools developed by the Stanford NLP Group. This open-source project, crafted in Java, provides powerful tools for analyzing human language text. It transforms text into a structured form by understanding the intricacies of language, which includes identifying the base forms of words, determining parts of speech, recognizing entities like companies or people's names, normalizing dates, interpreting numeric quantities, and understanding syntactic sentence structures. Besides English, CoreNLP extends its support to several languages, including Modern Standard Arabic, Chinese, French, German, Hungarian, Italian, and Spanish, although the depth of support varies.

CoreNLP's capabilities are invaluable for creating higher-level text understanding applications across academia, industry, and government. It integrates various types of analysis tools, making it possible to process text efficiently with minimal code.

Building CoreNLP

Provided Builds

Stanford CoreNLP releases new software versions several times a year, offering stable versions for users. The newest development code is also available for those interested in the latest updates.

Building with Ant

For users who prefer to compile the code manually, Ant can be employed:

1. Ensure Ant is installed on your system (Ant installation guide).
2. Navigate to the CoreNLP directory and compile the code using the ant command.
3. Build a jar file with the latest code using cd CoreNLP/classes ; jar -cf ../stanford-corenlp.jar edu.
4. Add dependencies located in CoreNLP/lib and CoreNLP/liblocal to your CLASSPATH.
5. Download the latest models for the languages you need, such as CoreNLP models, and include them in your CLASSPATH.

Building with Maven

Maven users can follow these steps:

1. Confirm Maven is installed (Maven installation guide).
2. In the CoreNLP directory, run mvn package to execute tests and build stanford-corenlp-4.5.4.jar.
3. Ensure to obtain the necessary models for your language and add them to your CLASSPATH.
4. For Maven projects, models should be installed into the Maven repository with specific commands, adapting the language in the command as needed.

Models Integration

The models are a crucial aspect of CoreNLP, containing language-specific resources. Users can access these models via direct download from links provided or through the Hugging Face Hub using git-lfs. For example, if working with French models, use:

# Ensure git-lfs is installed
git lfs install

git clone https://huggingface.co/stanfordnlp/corenlp-french

Users can find direct download links and additional resources for other languages as well.

Installation via Gradle

For Gradle users, integrating Stanford CoreNLP is straightforward. Modify your build.gradle file by adding the following dependency information:

dependencies {
    implementation 'edu.stanford.nlp:stanford-corenlp:4.5.5'
    // Add language-specific models if necessary
    implementation "edu.stanford.nlp:stanford-corenlp:4.5.5:models"
    implementation "edu.stanford.nlp:stanford-corenlp:4.5.5:models-english"
    implementation "edu.stanford.nlp:stanford-corenlp:4.5.5:models-english-kbp"
}

Replace "4.5.5" with your desired version if different.

Additional Resources

Users can browse the releases of Stanford CoreNLP on Maven Central and explore comprehensive documentation on the Stanford CoreNLP homepage. Additionally, community support through StackOverflow and the project's mailing lists offers avenues for questions and further interaction with the developer community.