cfierro/othello-synthetic

Othello (synthetic)

Uniformly-random legal Othello games -- a regeneration of the synthetic training data from Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task (Li et al., ICLR 2023), at the paper's own scale, since the original Google Drive release is no longer reachable.

Games are generated by the original Othello engine from likenneth/othello_world (vendored in this repo under third_party/othello_world/), driven by data/othello_game.py, which seeds each game by index so the dataset is reproducible and the multiprocessing workers stay independent.

The game

• Standard 8x8 Othello: four discs pre-placed in the centre, Black moves first, a move must bracket at least one contiguous line of opponent discs (in any of the 8 directions) between the new disc and one of your own, and every bracketed line flips.
• Every move here is legal but otherwise random -- uniform over the legal moves at each position. No strategy, no engine, no human games.
• Passing. A player with no legal move passes and the opponent moves again, so the colours in a game do not strictly alternate. Never infer the mover from the move index -- use the players column.
• A game ends when neither player can move, which is a full board (60 moves) or, occasionally, 59.

Notation

Cells use the upstream repo's own string form (permit_reverse): a lowercase row letter a-h followed by a column digit 1-8, e.g. d5, with flat board index row * 8 + col. Note the row comes first, which is transposed relative to standard Othello notation; it is kept so cell names, board indices and Li et al.'s own evaluation code line up without a translation layer.

Columns

• text — the moves in play order, comma separated, e.g. f5, f4, c3, .... The number of moves is the game's decision-point count.
• players — the colour that played each move, as a string of B/W of the same length, e.g. BWBWWB.... A repeated letter marks a pass by the other colour.
• num_moves — decision points in the game (59 or 60).
• n_passes — how many moves were reached because the other colour had to pass.

Splits

Split	Games	Decision points	Avg moves/game	Games with a pass	Passes
train	20,000,000	1,199,496,827	59.97	6,889,947 (34.4%)	8,924,951 (0.74%)
test	3,796,010	227,670,564	59.98	1,308,791 (34.5%)	1,696,278 (0.75%)

Split sizes are the paper's own (20,000,000 train, 3,796,010 validation). The two splits are disjoint by construction: train draws seeds from 0 upward, test from 1,000,000,000 upward, and games are deduplicated by move sequence across both.

Usage

from datasets import load_dataset
ds = load_dataset("cfierro/othello-synthetic")
game = ds["train"][0]
moves = [m.strip() for m in game["text"].split(",")]
colors = list(game["players"])   # "B"/"W" per move

Board state, legal moves and per-position replay: data/othello_game.py (decision_points, render).

Provenance

• Code: generated with data/push_othello_dataset.py @ 8bc64a1c1e.

  ⚠️ The working tree had uncommitted changes when this dataset was generated, so the linked commit may not exactly match the code that ran. Commit the generator before generating for a faithful link.

• Built: 2026-08-05T18:40:22

• Command:

python data/push_othello_dataset.py --out_dir /projects/nlp/data/constanzam/knowledge-ft/othello_gen_games --num_proc 64

• Resolved arguments:

{
  "repo": "cfierro/othello-synthetic",
  "out_dir": "/projects/nlp/data/constanzam/knowledge-ft/othello_gen_games",
  "train_games": 20000000,
  "test_games": 3796010,
  "test_seed_offset": 1000000000,
  "num_proc": 64,
  "no_dedup": false,
  "skip_push": false,
  "push_only": false,
  "dry_run": false,
  "private": false
}