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Read the following software repository codebase and documentation. Extract the exact requested identifier, command, or value. ### Context: According to a study by Robert <unk> , by 2002 there had been least eight adaptations of the play as a musical , though " never with conspicuous success " . The earliest such ver...
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37,118
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July 28, 1992
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37.9%
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American football
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472,027,235,000
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Linkin Park
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Karl Malone
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Agent Primitives Pilot: High-Entropy Extraction Dataset (305k Rows)

A high-fidelity agentic extraction dataset specifically curated and aligned for small, ultra-fast language and hybrid models (e.g., Liquid AI LFM2-1.2B-Extract and LFM3-1.7B).

All synthetic degeneration loops, streaming repetitions, and padded artifacts have been permanently pruned. Every target strictly satisfies the $\le 32$ token ceiling to force models into concise, hallucination-free primitive extraction.


1. Composition Summary (305,063 Total Clean Rows)

Primitive Samples Share Description & Benchmark Source Target Ceiling
INT 99,162 32.51% Deterministic integer answers (MetaMathQA) $\le 12$ tokens
SPAN 86,580 28.38% Verbatim factual document answer spans (SQuAD v2) $\le 32$ tokens
STRUCT 59,270 19.43% Compact JSON key-value extraction (LiquidAI/structured-extraction) $\le 32$ tokens
CODE 28,769 9.43% Linux commands & tool-calling arguments (Romit2004/LinuxCommands, Glaive) $\le 32$ tokens
STR 9,575 3.14% Scientific and technical string extraction (SciQ, IETF RFCs) $\le 20$ tokens
NOUL 8,553 2.80% Explicit non-hallucination abstentions ("null", BoolQ & missing schema fields) 1 token
CHOICE 7,214 2.36% Fast decision routing & tool name selection (Fastino fast-decisions) $\le 6$ tokens
REPLAY 5,940 1.95% Exact reproduction & verbatim state recovery (Databricks Dolly) $\le 32$ tokens

2. Distributed Cluster Execution (distlab Orchestration)

This dataset was processed and verified using the distlab distributed cluster engine across 32 idle compute nodes (384 CPU cores):

  • Master Node: 10.5.16.86 (orchestration, slicing, parquet encoding, and upload).
  • Worker Execution: 32 nodes executed pure standard-library workers strictly inside ~/.work/ without touching host directories.
  • Batch Dispatch: 32 jobs dispatched concurrently via distlab submit --batch (Batch ID: b_1031_185710_e3da).
  • Runtime: Completed in 4.8 seconds across 32 nodes (32/32 successful, 0 failed).
  • Target Verification: 0 target token violations (>32 tokens = 0.00%).

3. Quickstart & Usage

from datasets import load_dataset

# Load compact high-entropy shards directly:
ds = load_dataset("saidurga001301/agent-primitives-pilot-1k", data_dir="data_compact", split="train")

print(f"Total Rows: {len(ds):,}")
print("Sample:", ds[0])
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