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README.md

@@ -12,31 +12,6 @@ tags:
 - triples
 size_categories:
 - 1K<n<10K
-dataset_info:
-  features:
-  - name: subject
-    dtype: string
-  - name: predicate
-    dtype: string
-  - name: object
-    dtype: string
-  - name: object_type
-    dtype: string
-  - name: object_datatype
-    dtype: 'null'
-  - name: object_language
-    dtype: 'null'
-  splits:
-  - name: data
-    num_bytes: 29616925
-    num_examples: 154213
-  download_size: 2431122
-  dataset_size: 29616925
-configs:
-- config_name: default
-  data_files:
-  - split: data
-    path: data/data-*
 ---
 
 # NELL-995
@@ -49,20 +24,21 @@ Never-Ending Learning subset for link prediction
 
 ### Dataset Summary
 
-This dataset contains RDF triples from NELL-995 converted to HuggingFace dataset format
-for easy use in machine learning pipelines.
+This dataset contains RDF triples from NELL-995 converted to HuggingFace
+dataset format for easy use in machine learning pipelines.
 
 - **Format:** Originally tsv, converted to HuggingFace Dataset
 - **Size:** 0.12 GB (extracted)
 - **Entities:** ~75,492
 - **Triples:** 154,213
-- **Original License:** CC BY-NC
+- **Original License:**
+    CC BY-NC
 
 ### Recommended Use
 
 Semi-supervised learning benchmarks, noisy data experiments
 
-### Notes\n\nNAACL18 paper dataset. Contains raw.kb file with triples and evaluation splits. Format: tab-separated triples.
+### Notes: NAACL18 paper dataset. Contains raw.kb file with triples and evaluation splits. Format: tab-separated triples.
 
 
 ## Dataset Format: Lossless RDF Representation
@@ -131,7 +107,8 @@ for row in data:
 
 ### Converting Back to RDF
 
-The dataset can be converted back to any RDF format (Turtle, N-Triples, RDF/XML, etc.) with **zero information loss**:
+The dataset can be converted back to any RDF format (Turtle, N-Triples, RDF/XML,
+etc.) with **zero information loss**:
 
 ```python
 from datasets import load_dataset
@@ -186,11 +163,14 @@ This format preserves **100% of RDF information**:
 
 - ✅ **URIs**: Exact string representation preserved
 - ✅ **Literals**: Full text content preserved
-- ✅ **Datatypes**: XSD and custom datatypes preserved (e.g., `xsd:integer`, `xsd:dateTime`)
+- ✅ **Datatypes**: XSD and custom datatypes preserved
+    (e.g., `xsd:integer`, `xsd:dateTime`)
 - ✅ **Language Tags**: BCP 47 language tags preserved (e.g., `@en`, `@fr`, `@ja`)
-- ✅ **Blank Nodes**: Node structure preserved (identifiers may change but graph isomorphism maintained)
+- ✅ **Blank Nodes**: Node structure preserved (identifiers may change but
+    graph isomorphism maintained)
 
-**Round-trip guarantee**: Original RDF → HuggingFace → Reconstructed RDF produces **semantically identical** graphs.
+**Round-trip guarantee**: Original RDF → HuggingFace → Reconstructed RDF
+produces **semantically identical** graphs.
 
 ### Querying the Dataset
 
@@ -223,7 +203,8 @@ print(df["predicate"].value_counts())
 
 ### Dataset Format
 
-The dataset contains all triples in a single **data** split, suitable for machine learning tasks such as:
+The dataset contains all triples in a single **data** split, suitable for
+machine learning tasks such as:
 
 - Knowledge graph completion
 - Link prediction
@@ -250,7 +231,7 @@ The specification includes:
 - **Original Size**: 0.12 GB
 - **Conversion Tool**: [CleverErnie RDF Pipeline](https://github.com/CleverThis/cleverernie)
 - **Format Version**: 1.0
-- **Conversion Date**: 2025-11-06
+- **Conversion Date**: 2026-01-09
 
 
 ## Citation
@@ -267,13 +248,14 @@ This dataset was prepared using the CleverErnie GISM framework:
 
 ```bash
 # Download original dataset
-cleverernie download-dataset -d nell-995
+python scripts/rdf_dataset_downloader.py nell-995 -o datasets/
 
 # Convert to HuggingFace format
-python scripts/convert_rdf_to_hf_dataset.py \
+python scripts/convert_rdf_to_hf_dataset_unified.py \
     datasets/nell-995/[file] \
     hf_datasets/nell-995 \
-    --format tsv
+    --format tsv \
+    --strategy auto
 
 # Upload to HuggingFace Hub
 python scripts/upload_all_datasets.py --dataset nell-995
@@ -288,8 +270,9 @@ https://github.com/wenhuchen/KB-Reasoning-Data/archive/refs/heads/master.zip
 ### Conversion Details
 
 - Converted using: [CleverErnie GISM](https://github.com/cleverthis/cleverernie)
-- Conversion script: `scripts/convert_rdf_to_hf_dataset.py`
+- Conversion script: `scripts/convert_rdf_to_hf_dataset_unified.py`
 - Dataset format: Single 'data' split with all triples
+- Strategy: Auto-selected based on dataset size and format
 
 ### Maintenance