Update README.md

README.md

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 ---
-dataset_info:
-  features:
-  - name: header
-    dtype: string
-  - name: content
-    dtype: string
-  - name: is_substantive
-    dtype: bool
-  - name: function
-    dtype: string
-  - name: topic
-    dtype: string
-  - name: source_jurisdiction_type
-    dtype: string
-  - name: state
-    dtype: string
-  - name: city
-    dtype: string
-  - name: county
-    dtype: string
-  - name: document_id
-    dtype: string
-  - name: source_index
-    dtype: int64
-  splits:
-  - name: train
-    num_bytes: 5401159224
-    num_examples: 3027628
-  download_size: 2044428838
-  dataset_size: 5401159224
+pretty_name: LOCUS v1.0
+language:
+  - en
+task_categories:
+  - text-classification
+size_categories:
+  - 1M<n<10M
+tags:
+  - law
+  - legal-nlp
+  - local-government
+  - municipal-law
+  - ordinances
+  - classification
 configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+  - config_name: default
 ---
+
+# LOCUS v1.0
+
+## Dataset Summary
+LOCUS v1.0 is a chunk-level dataset of U.S. municipal and county law text labeled by legal function. Each eligible chunk is assigned a `function`, a binary `is_substantive` label, and all substantive provisions are assigned a `topic`.
+The dataset is intended for legal text research, local-law structure analysis, substantive filtering, and downstream taxonomy refinement.
+
+## Dataset Structure
+The unit of analysis is a text chunk derived from local law documents.
+
+## Scale
+Approximate scope for v1.0:
+- Total rows: `3,027,628`
+- Approximate substantive rows: `1,746,737`
+- Approximate non-substantive rows: `1,280,869`
+- Header-only rows excluded from model inference: `952,494`
+
+## Label Schema
+
+### Function
+Allowed values:
+- `Context`
+- `Rules`
+- `Process`
+- `Enforcement`
+- `Structural`
+
+### Substantive Indicator
+The released dataset enforces the following deterministic rule:
+- `is_substantive = 1` for `Rules` and `Enforcement`
+- `is_substantive = 0` for `Context`, `Process`, and `Structural`
+
+### Topic
+Used only when `is_substantive = 1`.
+
+Allowed values:
+- `Buildings`
+- `Business`
+- `Nuisance`
+- `Zoning`
+- `Other`
+
+## Recommended Uses
+LOCUS v1.0 is appropriate for:
+- legal text classification research
+- local law structure analysis
+- substantive versus non-substantive filtering
+- downstream taxonomy refinement
+- weakly supervised or human-in-the-loop legal NLP workflows
+
+## Out-of-Scope Uses
+LOCUS v1.0 should not be treated as:
+- legal advice
+- a substitute for human legal review
+- a complete census of all U.S. local law
+- a fully human-validated benchmark without additional auditing
+
+## Citation
+