| # Manifold UserModeling Benchmark (Belief WIP) |
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| This repository mirrors the Polymarket benchmark layout and currently focuses on **Belief-layer data preparation**. |
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| ## Folder Layout |
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| - `dataset/Belief/source/` |
| - `dataset/Belief/splits/` |
| - `dataset/Belief/support_set/` |
| - `benchmark/Belief/{direct,profile,retrieval}/` (placeholders for next stage) |
| - `metadata/` |
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| --- |
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| ## 1) Source Tables (`dataset/Belief/source/`) |
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| ### `data.csv` |
| User-market final belief master table (one row per `userId*marketId`). |
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| Key columns: |
| - `userId`, `marketId` |
| - `options_n` |
| - `dominant_option`, `dominant_net`, `dominant_share` |
| - `candidate_options_json` |
| - `candidate_net_json` |
| - `candidate_bets_json` |
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| Use this table as the primary supervised target source for Belief tasks. |
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| ### `option_accumulate.csv` |
| Candidate-level accumulate table (one row per `userId*marketId*option`). |
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| Key columns: |
| - `option_key` (`ANS:<answerId>` for multi-choice, `SIDE:YES/NO` for binary-like) |
| - `accumulate_net_amount` |
| - `bets_count` |
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| Use this when you need per-candidate decomposition rather than only the dominant option. |
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| --- |
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| ## 2) Query Splits (`dataset/Belief/splits/`) |
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| ### `train.csv`, `validation.csv`, `test.csv` |
| Rows are query `userId*marketId` samples split by **per-user market last-bet time** chronology. |
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| ### `split_summary.txt` |
| Split counts summary. |
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| ### `wallet_ids_experiment_2000.csv` |
| The sampled query user pool (2000 users, bucketed by `markets_per_user`). |
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| --- |
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| ## 3) Support Set (`dataset/Belief/support_set/`) |
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| ### `support_users.csv` |
| Support user list and user-level stats. |
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| ### `support_belief_final.csv` |
| Support users' final `user*market` belief summary (dominant/candidate aggregate view). |
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| ### `support_belief_option_accumulate.csv` |
| Support users' candidate-level accumulate records. |
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| ### `support_user_bets_chrono.csv` |
| Support users' **deduplicated bet events**, sorted by: |
| 1. `userId` |
| 2. `createdTime` |
| 3. `betId` |
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| Key columns include: |
| - `userId`, `createdTime`, `betId`, `marketId` |
| - `outcome`, `answerId`, `amount`, `shares` |
| - `probBefore`, `probAfter`, `isApi` |
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| ### `support_user_bets_index.csv` |
| Per-user row-range index into `support_user_bets_chrono.csv` for fast retrieval. |
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| Columns: |
| - `userId` |
| - `start_row_in_events_csv_1based_excluding_header` |
| - `end_row_in_events_csv_1based_excluding_header` |
| - `num_bets` |
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| --- |
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| ## How to Use (Current Stage) |
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| ### 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. |
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| ### 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` |
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| --- |
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| ## Notes |
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| - Current files are CSV for transparency and easier inspection. |
| - Next stage will generate `benchmark/Belief/direct`, `profile`, and `retrieval` artifacts aligned with Polymarket format. |
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