🧭 Getting Started

Welcome to Tag Me Maybe.

TMM is a lightweight, browser-based environment for annotation, exploration, and visual analysis of text data. It runs locally in your browser and does not require installation or login.

You can open one of the demo files to explore the interface, or import your own project files and continue working immediately.

1. Open tagmemaybe.org in your browser.
2. Download the sample file if you want to explore the demo workflow.
3. Click Launch demo or Open demo to enter the main interface.

💡 Tip: TMM works best when you treat exported JSON files as project snapshots. Even if you use autosave, regular exports are still a good habit.

📥 Importing Data

TMM supports two main import formats:

• .xlsx for importing raw texts or segment-based datasets,
• .json for reopening a full project with its segments, annotations, relations, available tags, available relation types, and other project settings.

To import a file:

1. Use the import controls in the bottom toolbar.
2. Select either an .xlsx file or a previously exported .json project file.
3. Wait until the text appears in the interface and the project is fully loaded.

💡 Tip: When importing raw text from .xlsx, make sure the file uses the expected column structure. When importing .json, treat that file as the full save state of your project.

✏️ Annotation Basics

In TMM, the text is divided into segments. Segments are the basic textual units displayed in the left column. From those segments, you can create one or more annotations shown on the right.

This distinction is important: a segment is the source text unit, while an annotation is your analytical object.

To create an annotation:

1. Click a segment in the left column to select it.
2. Choose an existing tag or type a custom one.
3. Add the text content of the annotation.
4. Confirm by clicking ➕ Add.

💡 Tip: One segment can contain multiple annotations. This is useful when a single utterance performs more than one function or contains several analytically relevant parts.

🔗 Relations and Hierarchy

TMM lets you connect annotations in two main ways: through relations and through hierarchical links.

Relations connect two annotations as separate analytical objects. Hierarchy organises annotations inside the same local structure, for example when one annotation is subordinate to another.

To create a relation:

1. Click the source annotation.
2. Choose Add relation.
3. Click the target annotation.
4. Select the relation type from the available list.

💡 Tip: Depending on the project setup, relations may later be explored in the annotation view, in the Visualizer, in the Debate Map, and in the Statistics tab.

🛠️ Editing and Reviewing

You can freely revise annotations and relations while working. TMM is designed for iterative annotation rather than one-pass tagging.

Typical editing actions include:

• editing the tag label,
• editing the text content of an annotation,
• changing the relation type,
• reviewing annotations through local details, visual cues, and relation displays.

To edit a relation:

1. Locate the relation pill connected to the annotation.
2. Click the ✏️ icon.
3. Select a new relation type from the list.

💡 Tip: Review is easier when you combine local editing with broader views such as Explorer, Statistics, Visualizer, and Debate Map.

🔎 Explorer

The Explorer tab is designed for browsing, filtering, and inspecting annotations in a more analytical way than simple scrolling.

It is especially useful when your project becomes too large to inspect comfortably in the main annotation view.

You can:

• switch between different browsing modes,
• filter results by text, speaker, segment, tag, or other metadata,

💡 When to use it: Use Explorer when you want to find patterns, check consistency, or inspect a specific class of annotations without manually scanning the whole document.

📊 Statistics

The Statistics tab provides quantitative overviews of your project. It helps you move from individual annotations to the structure of the dataset as a whole.

Depending on the project configuration, Statistics may include:

• basic counts of segments, annotations, and relations,
• tag and relation distributions,
• coverage and validation-oriented views,
• speaker-based summaries,
• agreement-related sections in multi-annotator workflows.

Use this tab both for descriptive overview and for quality control.

💡 Good practice: Open Statistics not only at the end of a project, but also during annotation. It is one of the fastest ways to detect imbalance, inconsistency, or unexpected gaps.

🕸️ Visualizer

The Visualizer tab displays your annotations and relations as an interactive graph.

This view is useful when you want to inspect neighbourhoods, trace local structures, or understand how one part of the annotation network connects to another.

• Use it to inspect relation structure from a graph perspective.
• Use filtering options to focus on selected relation types or local subgraphs.
• Use it when the annotation view becomes too linear for the question you are asking.

🗺️ Debate Map

The Debate Map offers a more presentation-oriented visual view of annotated material. Compared with the Visualizer, it is often easier to read as a structured explanatory display.

This tab is especially useful when you want to show argumentative or discourse structure to other readers, not only inspect it yourself.

• Use it when you want a bridge between close reading and visual explanation.

💾 Export and Saving

TMM stores your work locally in the browser and also allows you to export full project files.

In practice, an exported JSON file is also your save file.

How saving works:

• the application auto-saves your progress locally,
• Export JSON creates a portable snapshot of the project,
• that JSON file can later be imported again to continue your work,
• Download Autosave can be used as an additional backup copy.

💡 Tip: For important projects, keep several exported JSON versions instead of relying on a single latest file.

💡 Tips and Good Practices

• Export JSON regularly, especially before major editing changes.
• Use smaller test files when experimenting with new tagsets or workflows.
• Review your work in more than one tab: annotation, Explorer, Statistics, Visualizer, and Debate Map each reveal different issues.
• Keep your labels and relation choices consistent across the dataset.
• Treat Guide as a practical entry point, but validate project-specific decisions against your annotation scheme.