# Data Mining

## LingoAI Community Mining Mechanism

**Total Allocation: 45,000,000,000 Tokens**

LingoAI adopts a **long-term, contribution-driven community mining model** designed to support sustainable growth of a global AI data infrastructure.

Community mining tokens are released over **20 years**, divided into **three phases**, each aligned with the maturity of the network.

The system prioritizes **real-world data contribution, long-term participation, and gradual decentralization**, rather than short-term incentives.

| Phase     | Duration     | Focus                    | Allocation   |
| --------- | ------------ | ------------------------ | ------------ |
| Phase 1   | Years 1–5    | Network Scale            | 45% (20.25B) |
| Phase 2   | Years 6–10   | Scale × Quality          | 30% (13.5B)  |
| Phase 3   | Years 11–20  | Quality & Sustainability | 25% (11.25B) |
| **Total** | **20 Years** |                          | **45B**      |

<table><thead><tr><th width="269.67083740234375">Task</th><th width="371.6328125">Percentage of total supply</th></tr></thead><tbody><tr><td>Data Contributors</td><td>40%</td></tr><tr><td>Data Processing</td><td>20%</td></tr><tr><td>Cross-lingual LLM Development</td><td>10%</td></tr><tr><td>Validators</td><td>30%</td></tr></tbody></table>

### Phase 1: Network Scale (Years 1–5)

**Allocation:** 20.25B tokens (45%)

#### Objective

Phase 1 focuses on **rapid global network expansion**, encouraging large-scale participation from contributors across languages, regions, and data types.

The goal is to establish LingoAI as a **global data entry layer** for multilingual and multimodal AI.

#### Key Characteristics

* Incentives prioritize **contribution volume**
* Low participation barriers
* Strong early rewards to bootstrap the ecosystem
* No instant liquidity: rewards are **recorded first, released gradually**

#### Annual Emission Distribution (Phase 1)

<table><thead><tr><th width="91.85986328125">Year</th><th>% of Phase 1</th><th>Tokens Released</th></tr></thead><tbody><tr><td>Year 1</td><td>28%</td><td>5.67B</td></tr><tr><td>Year 2</td><td>24%</td><td>4.86B</td></tr><tr><td>Year 3</td><td>20%</td><td>4.05B</td></tr><tr><td>Year 4</td><td>16%</td><td>3.24B</td></tr><tr><td>Year 5</td><td>12%</td><td>2.43B</td></tr><tr><td><strong>Total</strong></td><td><strong>100%</strong></td><td><strong>20.25B</strong></td></tr></tbody></table>

### Phase 2: Scale × Quality (Years 6–10)

**Allocation:** 13.5B tokens (30%)

#### Objective

Phase 2 balances **continued growth** with **improving data quality**.

As the network matures, incentives increasingly favor:

* High-quality data
* Scarce languages and domains
* Contributors with consistent participation histories

#### Key Characteristics

* Emissions continue to decline gradually
* Quality multipliers are introduced
* Usage-based acceleration begins (data that is used unlocks faster)
* Volume alone is no longer sufficient for optimal rewards

#### Annual Emission Distribution (Phase 2)

| Year      | % of Phase 2 | Tokens Released |
| --------- | ------------ | --------------- |
| Year 6    | 28%          | 3.78B           |
| Year 7    | 24%          | 3.24B           |
| Year 8    | 20%          | 2.70B           |
| Year 9    | 16%          | 2.16B           |
| Year 10   | 12%          | 1.62B           |
| **Total** | **100%**     | **13.5B**       |

### Phase 3: Quality & Sustainability (Years 11–20)

**Allocation:** 11.25B tokens (25%)

#### Objective

Phase 3 transforms community mining into a **long-term sustainability mechanism**.

Tokens become increasingly scarce, and rewards are tightly coupled to:

* Data quality
* Real-world usage
* Long-term contribution loyalty

This phase ensures that the network remains active and valuable **decades after launch**.

#### Key Characteristics

* Strong emphasis on **usage-driven rewards**
* High-quality and rare data prioritized
* Long-term contributors benefit from loyalty weighting
* Emissions never drop to zero, preserving ongoing incentives

#### Annual Emission Distribution (Phase 3 – 10 Years)

| Year      | % of Phase 3 | Tokens Released |
| --------- | ------------ | --------------- |
| Year 11   | 15%          | 1.69B           |
| Year 12   | 14%          | 1.58B           |
| Year 13   | 13%          | 1.46B           |
| Year 14   | 12%          | 1.35B           |
| Year 15   | 11%          | 1.24B           |
| Year 16   | 10%          | 1.13B           |
| Year 17   | 9%           | 1.01B           |
| Year 18   | 7%           | 0.79B           |
| Year 19   | 5%           | 0.56B           |
| Year 20   | 4%           | 0.45B           |
| **Total** | **100%**     | **11.25B**      |

***

### Epoch-Based Distribution Model

All community mining rewards are distributed using an **epoch-based system**.

* **1 Epoch = 30 days**
* Contributions are recorded continuously during the epoch
* Rewards are calculated and allocated at epoch end
* Tokens enter a **delayed release schedule**, not immediate circulation

This design:

* Prevents short-term exploitation
* Reduces sell pressure
* Aligns rewards with long-term participation

***

### Visual Emission Curve (Conceptual)

```
Token Emission Intensity
│
│ Phase 1 █████████████▇▆▅
│ Phase 2        ▇▆▅▅▄
│ Phase 3              ▄▃▃▂▂▁
│
└────────────────────────────────── Time (20 Years)
```

### Summary

The LingoAI community mining model is designed as a **20-year incentive framework** that evolves alongside the network:

* Phase 1 builds global scale
* Phase 2 improves quality and utility
* Phase 3 ensures long-term sustainability


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.lingoai.io/introduction/lingoai-token/data-mining.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
