license: cc0-1.0
language:
- en
tags:
- chess
- pgn
- puzzles
- tactics
pretty_name: Chess Puzzles with PGN Context
size_categories:
- 1K<n<10K
Chess Puzzles with PGN Context
Tactical chess puzzles drawn from the Lichess Open Puzzle Database, augmented with full PGN game context reconstructed from the source Lichess games.
Each record presents a middlegame position as a PGN move sequence — the same format used to train PGN language models like kn1ght — together with the engine-validated best move as the label.
Dataset Summary
- 5,000 puzzles with reconstructed PGN context
- Rating range: 1200–1900 (mean: 1540)
- Themes:
middlegame,short,advantage,crushing,long,mate,fork,kingsideAttack(middlegame only; opening/endgame excluded) - Splits: 80% train / 10% validation / 10% test
Schema
| Column | Type | Description |
|---|---|---|
puzzle_id |
string | Lichess puzzle ID |
game_id |
string | Lichess game ID (source of PGN context) |
rating |
int32 | Puzzle difficulty (Lichess Glicko-2 rating) |
themes |
list[string] | Tactical theme tags (e.g. fork, pin, skewer) |
pgn_context |
string | PGN move text up to (not including) the puzzle move |
fen |
string | Board position at start of puzzle in FEN notation |
best_move_uci |
string | Correct first move in UCI notation |
best_move_san |
string | Correct first move in SAN notation |
Usage
from datasets import load_dataset
ds = load_dataset("InterwebAlchemy/chess-puzzles-pgn")
# Each example:
# {'pgn_context': '1.e4 e5 2.Nf3 Nc6 ... 18.Rxd4',
# 'best_move_san': 'Nf6+',
# 'rating': 1487,
# 'themes': ['fork', 'middlegame']}
How PGN context is reconstructed
For each Lichess puzzle:
- The source game PGN is fetched from
lichess.org/api/game/<id> - The game is replayed move by move until the board FEN matches the puzzle FEN
- The move-text up to that point is stored as
pgn_context - The first solution move (UCI → SAN) is stored as
best_move_san
Puzzles where the FEN could not be located in the source game are discarded.
Intended use
Evaluating and fine-tuning PGN language models on tactical positions. The pgn_context
field can be fed directly to any model that generates chess moves as PGN continuations.
Licensing
This dataset is derived from the Lichess Open Database, which is released under CC0 1.0 (Public Domain). This derived dataset is also released under CC0 1.0.