Add pruned Wikidata binary and README

README.md

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 ---
 license: cc-by-4.0
+task_categories:
+- graph-ml
+language:
+- en
+tags:
+- semantic-network
+- knowledge-graph
+- wikidata
+- graph-ml
+- semantic-inference
+- token-compression
+pretty_name: 'zelph Binaries: Semantic Networks from Knowledge Bases (e.g., Wikidata)'
+size_categories:
+- 100M<n<1B
 ---
+
+# zelph Binaries Dataset
+
+This dataset provides pre-compiled binary files (.bin) for use with [zelph](https://github.com/acrio/zelph), a sophisticated semantic network system.
+These binaries are derived from large knowledge bases like Wikidata, optimized for fast loading and efficient querying.
+
+## Dataset Description
+
+zelph binaries enable users to work with semantic networks without the need to import raw dumps (e.g., JSON files), which can take hours.
+Instead, these .bin files load in minutes, though they require substantial RAM.
+
+The dataset includes both full and pruned variants:
+
+- **Full binaries**: Contain the complete network, suitable for comprehensive use but demanding high RAM (Wikidata: ~ 210 GB RAM).
+- **Pruned binaries**: Reduced versions with removed domains (e.g., biology, chemistry, astronomy) to lower RAM requirements (~ 16 GB RAM) while preserving core connections.
+
+For detailed information on each binary, including sizes, creation dates, pruning details, and updates, visit [https://zelph.org/binaries](https://zelph.org/binaries).
+
+## How to Use
+
+1. Download the desired .bin file from this dataset.
+2. In zelph interactive mode, load it with:
+   ```
+   .load /path/to/your-file.bin
+   ```
+3. Run queries, define rules, perform inferences or run complete scripts (see [zelph on GitHub](https://github.com/acrion/zelph?tab=readme-ov-file#performing-inference) for details).
+
+## LLM-Friendly Outputs
+
+zelph can generate rule-based inferences in a compressed text format optimized for LLM training or processing.
+This uses a token encoder that maps Wikidata IDs (Q/P) to compact UTF-8 symbols (CJK range), reducing input length while preserving structure.
+
+This feature is currently focused on Wikidata, but it can be adapted for similar use cases.
+Use it to export inferences from loaded binaries for LLM datasets – see the [command documentation on GitHub](https://github.com/acrion/zelph?tab=readme-ov-file#exporting-deduced-facts-to-file) for details.
+
+## Citation
+If you use this dataset, cite as:
+```
+@dataset{zelph,
+  author = {Stefan Zipproth},
+  title = {zelph Binaries Dataset},
+  year = {2026},
+  url = {https://huggingface.co/datasets/acrion/zelph}
+}
+```

wikidata-20251222-pruned.bin

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+oid sha256:49c6b5553bb93f2c0909c8b6c86cf02a12dd076c550b0b0b7567b1d542ca832d
+size 4350008326