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Browse files- README.md +48 -10
- data/test-00000-of-00001.parquet +2 -2
- data/train-00000-of-00001.parquet +2 -2
- data/validation-00000-of-00001.parquet +2 -2
README.md
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size_categories:
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- 1K<n<10K
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pretty_name: NBA Quarter Events
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dataset_description:
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---
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# NBA Quarter Events
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size_categories:
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- 1K<n<10K
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pretty_name: NBA Quarter Events
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dataset_description: Curated per-quarter NBA play-by-play sequences from the 2024-25
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regular season, designed for temporal point process (TPP) and marked temporal point
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process (MTPP) modeling. Each sequence represents one quarter (Q1-Q4) of a single
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game, with the prediction target being the play type of the next event. Sequences
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are filtered to keep only quarters with 90-110 events, ensuring consistent sequence
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lengths. Rich narrative type_text descriptions provide fully descriptive context
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— shot style and distance, make/miss results, offensive/defensive rebound classification,
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full team names on every event, and timeout types — enabling an LLM to predict the
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next event type from the sequence alone.
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: validation
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path: data/validation-*
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- split: test
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path: data/test-*
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dataset_info:
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features:
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- name: seq_idx
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dtype: int64
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- name: seq_len
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dtype: int64
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- name: description
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dtype: string
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- name: metadata
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dtype: string
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- name: time_since_start
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list: float64
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- name: time_since_last_event
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list: float64
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- name: type_event
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list: string
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- name: type_text
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list: string
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splits:
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- name: train
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num_bytes: 40959139
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num_examples: 2296
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- name: validation
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num_bytes: 5104124
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num_examples: 286
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- name: test
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num_bytes: 5095473
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num_examples: 286
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download_size: 8628235
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dataset_size: 51158736
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---
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# NBA Quarter Events
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data/test-00000-of-00001.parquet
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:b78ab060a7693ad6c15739f444f680b620f24fa600768bc24137a3e6cecef4fb
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size 884252
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data/train-00000-of-00001.parquet
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size 6862404
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data/validation-00000-of-00001.parquet
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size 881579
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