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| license: mit |
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| # Fused Patent + arXiv Technical Clustering Dataset (Deterministic, Quality-Gated) |
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| ## Overview |
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| This dataset is the output of a zero-touch technical clustering pipeline built over a fused corpus of patent text and arXiv-style research text. |
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| The pipeline is fully deterministic from ingest through release and is designed to run end-to-end without manual curation or mid-run intervention. All artifacts, cluster assignments, and release decisions are derived from the same run. |
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| This is not a curated dataset. It is a large-scale fused technical corpus that has been **deterministically analyzed and quality-gated** to isolate the portion that behaves like a semantic clustering dataset. |
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| ## Key Stats |
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| * **Total labeled rows:** 9,063,272 |
| * **Raw clusters (pre-filter):** 422 |
| * **Release clusters (post-filter):** 147 |
| * **Retained rows:** 3,881,329 |
| * **Retention rate:** 42.82% |
| * **Shards:** 91 (labels / embeddings / chunks) |
| * **Size:** ~20+ GB compressed |
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| ## Pipeline Summary |
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| The dataset was produced by a staged, resumable pipeline with Postgres acting as a control plane. |
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| ### Core stages |
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| * Ingest and normalize fused patent + arXiv text |
| * Chunk-level embedding |
| * Embedding clustering |
| * Shard-level processing with persistent state |
| * Reducer-tree merge into global clusters |
| * Global assignment + BM25 artifact generation |
| * Deterministic inspection and release gating |
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| ## System Design |
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| The pipeline is built to operate under real constraints (long runtimes, memory pressure, interruptions), not ideal notebook conditions. |
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| ### Control plane (Postgres) |
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| * Task leasing and discovery |
| * Heartbeats and worker liveness |
| * Stage state tracking (not-ready / running / done / failed) |
| * Reducer-tree coordination and staged unblocking |
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| ### Failure-aware execution |
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| * Distinguishes between: |
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| * true OOM |
| * bad allocation |
| * killed process |
| * general memory pressure |
| * Descending batch ladder (deterministic step-down on failure) |
| * Proactive downshifting based on resource pressure |
| * Resumable state across interruptions |
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| ### Reducer-tree merge |
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| * Progressive level-by-level reduction |
| * Final stage unblocked only after upstream completion |
| * Prevents global merge bottlenecks |
| * Avoids downstream fan-out gaps |
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| ## Deterministic Quality Gating |
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| The raw clustering output was **not** treated as valid by default. |
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| A full deterministic inspection pass across all 422 clusters produced: |
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| * **147 coherent clusters** |
| * **107 mixed clusters** |
| * **168 metadata-heavy clusters** |
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| ### Filtering decision |
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| For the release dataset: |
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| * **Kept:** coherent clusters only |
| * **Dropped:** mixed + metadata-heavy clusters |
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| This was done without: |
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| * re-embedding |
| * hand labeling |
| * manual cluster editing |
| * modifying the original run |
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| All decisions are reproducible from pipeline outputs. |
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| ## Metadata Leakage |
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| A large portion of clusters were dominated by ingestion or wrapper fields such as: |
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| * `source_file` |
| * `record_hash` |
| * `raw_meta_json` |
| * `authors_parsed` |
| * `published_date` |
| * similar structural tokens |
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| These are not errors in the source data, but they degrade semantic clustering if left unfiltered. |
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| Explicit detection and removal of these clusters is a core part of the release process. |
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| ## Dataset Structure |
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| The release package includes filtered artifacts aligned to the retained clusters: |
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| * `labels/` — cluster assignments |
| * `chunks/` — source text chunks |
| * `embeddings/` — embedding vectors |
| * `microclusters/` — original microcluster outputs (for provenance) |
| * `global/` — cluster summaries, BM25 artifacts, reference data |
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| All components are consistent with the same filtered subset. |
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| ## What This Dataset Is |
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| * A **deterministically derived** technical clustering dataset |
| * A **fused patent + research corpus** with broad technical coverage |
| * A **quality-gated subset** of a larger clustering run |
| * A **reproducible artifact** tied to a single pipeline execution |
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| ## What This Dataset Is Not |
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| * Not manually curated |
| * Not hand-labeled |
| * Not cleaned via ad-hoc scripts |
| * Not a “perfect” semantic dataset |
| * Not independent from its pipeline (the pipeline defines it) |
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| ## Example Cluster Themes |
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| Cluster naming was derived deterministically from top terms. Example themes include: |
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| * wireless communication systems |
| * semiconductor substrates and layers |
| * chemical compounds and formulations |
| * neural networks and data processing |
| * vehicle control systems |
| * signal processing and circuits |
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| ## Intended Use |
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| * Retrieval / RAG experiments |
| * Technical topic clustering |
| * Cross-domain similarity analysis |
| * Large-scale embedding evaluation |
| * Downstream filtering / refinement pipelines |
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| ## Notes |
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| This dataset represents the **release-grade subset** of the full run. The original unfiltered output (422 clusters) is intentionally not presented as the primary artifact. |
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