How to Configure and Customize MMAX2 Annotation Tool for Your Corpus

A Beginner’s Guide to MMAX2 Annotation ToolMMAX2 is a free, Java-based annotation tool designed for creating and editing linguistic annotations (especially multi-layer and hierarchical annotations) over text corpora. It’s widely used in computational linguistics and discourse analysis for marking up structures like coreference, discourse segments, syntactic constituents, named entities, and more. This guide walks you through what MMAX2 does, how it’s organized, common workflows, practical tips, and resources to get you started.

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What MMAX2 Is and When to Use It

MMAX2 is a desktop application that focuses on flexible, XML-backed annotation of texts. It’s particularly useful when you need:

• Multi-layer annotations (several independent annotation tiers over the same text).
• Hierarchical annotations where annotations can nest or link across tiers.
• Precise control over annotation schemas and visual presentation.
• An offline tool with exportable XML that integrates into NLP pipelines.

MMAX2 is not ideal if you need an actively maintained cloud platform, built-in machine-learning-assisted annotation, or collaborative real-time annotation out of the box.

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Main Concepts and Components

• Corpus: The set of text documents you annotate. MMAX2 organizes corpora in a folder structure with XML files that represent documents and annotation levels.
• Markables: The basic annotation unit in MMAX2. A markable represents a span of text (for named entities, noun phrases, segments, etc.). Each markable belongs to an annotation level (tier).
• Annotation Levels (Tiers): Separate layers for different annotation types (e.g., NP-level, coreference-level, discourse-level). Levels may reference other levels.
• Markable Attributes: Properties assigned to markables (e.g., type, number, gender, role).
• Linking/Relations: Coreference chains or other relations are represented via attributes that reference markable IDs.
• Visual Configurations: Display settings (colors, borders, stacking) for how markables appear in the GUI.

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Installing and Launching MMAX2

1. Prerequisites: Install a compatible Java Runtime Environment (JRE). MMAX2 runs on Java 8 and often works on later versions, but if you hit issues, try Java 8.
2. Download: Obtain the MMAX2 distribution (usually a ZIP or TAR file) from university or project archives.
3. Unpack: Extract the files to a working directory; the directory structure contains folders like config, corpora, and the MMAX2 executable JAR.
4. Launch: Run MMAX2 with a command like:

   
   java -jar MMAX2.jar 

   (or double-click the JAR if your OS supports it).

If Java reports security warnings, allow the app to run for local/offline use.

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Creating a New Corpus

1. In the MMAX2 GUI, choose to create a new corpus or copy an example corpus in the distribution.

2. Corpus directory will contain:

   • raw text files (usually .txt),
   • a signal file (often .signal) that holds the text for annotation,
   • a project configuration file (project.xml),
   • annotation level files (.mmax2 or XML level files),
   • markable files (.mmax2.markables.xml).

3. Prepare your raw texts. MMAX2 expects a plain-text signal; special characters and encodings should be handled consistently (UTF-8 recommended).

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Defining Annotation Levels and Schema

1. Create annotation levels for each kind of annotation you need (e.g., Token, Chunk, NP, Coref).
2. For each level, define markable attributes (e.g., category, head, IDREF for references). Typical attributes for coreference: coref_id or antecedent.
3. Configure visual settings so annotators can quickly distinguish tiers by color and layout.

Configuration is done through XML files in the corpus folder or via the GUI level-editor. Keep schemata consistent across documents.

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Basic Annotation Workflow

1. Open a document (signal) from your corpus in MMAX2.
2. Select the annotation level you’ll work on (e.g., NP-level).
3. Create markables by selecting text spans and assigning attribute values (you can use keyboard shortcuts).
4. For coreference or relations, create markables for mentions and link them using IDREFs or chain attributes. MMAX2 supports creating chain views that group markables into coreference clusters.
5. Save frequently — MMAX2 writes XML files for each level and markable set.

For efficiency: use copy/paste of attributes, keyboard-driven navigation, and batch attribute setting when possible.

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Advanced Features

• Standoff annotations: Markables are stored separately from the signal text, which avoids modifying the original files.
• Hierarchical markables: Annotate nested structures (e.g., NP inside VP) and reference parent/child relationships.
• Scripting and export: The XML output is easy to parse with scripts (Python, Perl) to convert annotations into formats like CoNLL, JSON, or custom schemas.
• Interoperability: Because MMAX2 uses XML, bridging to other tools is straightforward. You can write XSLT or use XML libraries to transform markables.

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Exporting and Using Annotations in NLP Pipelines

1. Locate the markables XML files in the corpus folder.
2. Parse XML to extract spans, attributes, and relation IDs. Typical libraries: lxml or ElementTree in Python.
3. Convert to your desired format (e.g., CoNLL for coreference: mention spans with cluster IDs).
4. Integrate with training/evaluation scripts for tasks like coreference resolution, entity recognition, or discourse parsing.

Example (Python, extracting basic markable info):

from lxml import etree tree = etree.parse('mycorpus/mydoc.mmax2.markables.xml') for markable in tree.findall('.//markable'):     m_id = markable.get('id')     start = markable.get('span').split('/')[0]     end = markable.get('span').split('/')[1]     attrs = {child.get('name'): child.get('value') for child in markable.findall('.//attribute')}     print(m_id, start, end, attrs) 

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Common Pitfalls and Troubleshooting

• Encoding issues: Ensure UTF-8 consistently; mismatched encodings break parsing.
• Java compatibility: If MMAX2 crashes, try Java 8.
• Overlapping tiers: Visual clutter can happen with many overlapping markables; tune colors, transparency, and stacking rules.
• Broken references: If markable IDs get out of sync, relations won’t render correctly—use the built-in validation features or write small scripts to check referential integrity.

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Best Practices for Annotation Projects

• Create a clear annotation manual describing markable definitions, attribute values, and edge cases.
• Do a pilot annotation on a subset to refine schema and GUI settings.
• Use version control (git) or regular backups for your corpus folder.
• If multiple annotators work separately, define merging procedures and conflict resolution rules.
• Automate repetitive checks (e.g., all coreference chains have at least one mention).

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Resources and Further Reading

• MMAX2 distribution package (contains examples and sample corpora).
• Papers and tutorials from computational linguistics courses that use MMAX2 for coreference/discourse annotation.
• XML parsing libraries and scripts to convert MMAX2 output to common formats (CoNLL, BioC, etc.).
• Community forums and academic groups—search for “MMAX2 coreference tutorial” or sample corpora to practice.

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If you want, I can: provide a ready-to-use project folder structure, generate example XML markable files for a short sample text, or convert a small MMAX2 markables file into CoNLL format. Which would you like?