# Manifold UserModeling Benchmark (Belief WIP)

This repository mirrors the Polymarket benchmark layout and currently focuses on **Belief-layer data preparation**.

## Folder Layout

- `dataset/Belief/source/`
- `dataset/Belief/splits/`
- `dataset/Belief/support_set/`
- `benchmark/Belief/{direct,profile,retrieval}/` (placeholders for next stage)
- `metadata/`

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## 1) Source Tables (`dataset/Belief/source/`)

### `data.csv`
User-market final belief master table (one row per `userId*marketId`).

Key columns:
- `userId`, `marketId`
- `options_n`
- `dominant_option`, `dominant_net`, `dominant_share`
- `candidate_options_json`
- `candidate_net_json`
- `candidate_bets_json`

Use this table as the primary supervised target source for Belief tasks.

### `option_accumulate.csv`
Candidate-level accumulate table (one row per `userId*marketId*option`).

Key columns:
- `option_key` (`ANS:<answerId>` for multi-choice, `SIDE:YES/NO` for binary-like)
- `accumulate_net_amount`
- `bets_count`

Use this when you need per-candidate decomposition rather than only the dominant option.

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## 2) Query Splits (`dataset/Belief/splits/`)

### `train.csv`, `validation.csv`, `test.csv`
Rows are query `userId*marketId` samples split by **per-user market last-bet time** chronology.

### `split_summary.txt`
Split counts summary.

### `wallet_ids_experiment_2000.csv`
The sampled query user pool (2000 users, bucketed by `markets_per_user`).

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## 3) Support Set (`dataset/Belief/support_set/`)

### `support_users.csv`
Support user list and user-level stats.

### `support_belief_final.csv`
Support users' final `user*market` belief summary (dominant/candidate aggregate view).

### `support_belief_option_accumulate.csv`
Support users' candidate-level accumulate records.

### `support_user_bets_chrono.csv`
Support users' **deduplicated bet events**, sorted by:
1. `userId`
2. `createdTime`
3. `betId`

Key columns include:
- `userId`, `createdTime`, `betId`, `marketId`
- `outcome`, `answerId`, `amount`, `shares`
- `probBefore`, `probAfter`, `isApi`

### `support_user_bets_index.csv`
Per-user row-range index into `support_user_bets_chrono.csv` for fast retrieval.

Columns:
- `userId`
- `start_row_in_events_csv_1based_excluding_header`
- `end_row_in_events_csv_1based_excluding_header`
- `num_bets`

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## How to Use (Current Stage)

### Belief supervised training
- Use `dataset/Belief/splits/{train,validation,test}.csv` as query samples.
- Use `dominant_option` (or candidate distribution fields) from source as labels.

### Retrieval-style setup
- Query side: split files (`train/val/test`).
- Support side:
  - User-level belief memory: `support_belief_final.csv`
  - Event-level memory: `support_user_bets_chrono.csv` + `support_user_bets_index.csv`

---

## Notes

- Current files are CSV for transparency and easier inspection.
- Next stage will generate `benchmark/Belief/direct`, `profile`, and `retrieval` artifacts aligned with Polymarket format.