Generative extraction
LLM implementation is summarized at the experimental level
ChatGPT, Gemma, and Qwen generate structured text conditioned by extraction prompts. Gemma and Qwen were served through llama.cpp with quantized GGUF checkpoints, 65,536-token context, four parallel slots, Vulkan execution, and reasoning disabled. ChatGPT was recorded as “model 5.6 on high”; provider build and sampling trace were not archived.
Sparse mixture of experts
Gemma and Qwen route tokens through selected experts
The router assigns token representation hₜ to a small top-K subset of experts. Sparse routing changes active compute, capacity, load balance, and quantization sensitivity. Because there is no dense sibling control, router telemetry, or repeated seed design, the observed Gemma–Qwen difference cannot be attributed causally to MoE topology.
Reasoning controls
Reasoning-disabled and reasoning-enabled extraction are distinct treatments
Reasoning-disabled decoding can reduce latency and unsupported elaboration but may weaken reconciliation across distant evidence and schema constraints. Reasoning-enabled decoding may improve planning and self-checking, yet can increase token cost, paraphrase, and unsupported completion. The current local runs used reasoning off; the study therefore cannot estimate a reasoning effect without a factorial rerun.
HNLP and BERT have no autoregressive reasoning mode. Their corresponding treatment variables are dictionary versions, synonym expansion, optional OpenNLP resources, chunk windows, thresholds, label batches, mapping constraints, and backfill.
Model-selection programme
Alternative architectures to test
Layout-aware encoders
LayoutLM-family systems test whether columns, tables, and spatial headings improve reconstruction.
Dense controls
Dense siblings of Gemma or Qwen isolate sparse-routing effects more credibly than cross-family comparison.
Sequence models
Transformer-CRF or BiLSTM-CRF baselines provide fixed-label sequence constraints and transparent annotation requirements.
Constrained seq2seq
Schema-constrained generation tests long-range synthesis while limiting malformed output.