update

INFO.md

@@ -0,0 +1,99 @@
+# YAGO 4.5 Dataset (English subset for LLM fine-tuning)
+
+## Dataset Description
+This datasets contains triples filtered from yago-facts.ttl and
+yago-beyond-wikipedia.ttl in the YAGO 4.5 dataset. The SPARQL query
+used to filter the triples is in `raw/filter.sparql`. This represents
+a subset of the YAGO 4.5 dataset maintaining only English labels. 
+
+I remapped some schema.org URIs to use the
+`http://yago-knowledge.org/resource/` which were not present in the
+schema.org vocabulary.  I also removed schema:sameAs and owl:sameAs
+relations from this dataset, as well as triples with xsd:anyURI object
+literals, as my goal is to use this dataset for fine-tuning a large
+language model for knowledge graph completion and I do not want
+to train the base model to predict these kind of relations.
+
+### Overview
+
+YAGO 4.5 is the latest version of the YAGO knowledge base. It is
+based on Wikidata — the largest public general-purpose knowledge
+base. YAGO refines the data as follows:
+
+* All entity identifiers and property identifiers are human-readable.
+* The top-level classes come from schema.org — a standard repertoire
+  of classes and properties maintained by Google and others. The lower
+  level classes are a careful selection of the Wikidata taxonomy.
+* The properties come from schema.org.
+* YAGO 4.5 contains semantic constraints in the form of SHACL. These
+  constraints keep the data clean, and allow for logical reasoning on
+  YAGO. 
+
+
+### Dataset Structure
+The dataset is structured as follows:
+
+- **raw/yago-taxonomy.ttl:** Contains the `rdfs:subClassOf` relations
+  for YAGO and the prefix mappings for the N-Triples.
+- **raw/facts.tar.gz:** Compressed file containing chunks of the
+  dataset in N-Triples format, representing the factual knowledge in
+  YAGO. 
+
+### Features
+
+Each RDF triple in the dataset is represented with the following features:
+
+- **subject:** The subject of the triple, representing the entity.
+- **predicate:** The predicate of the triple, representing the
+  relationship between the subject and object.
+- **object:** The object of the triple, representing the entity or
+  value linked by the predicate.
+
+### Splits
+
+The dataset is logically divided into multiple chunks, each containing
+a subset of RDF triples. Users can load specific chunks or the entire
+dataset based on their requirements.
+
+## Usage
+
+### Loading the Dataset
+
+The dataset can be loaded using the Hugging Face `datasets` library as follows:
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('wikipunk/yago-4.5-en', num_proc=4)
+```
+
+### Accessing the YAGO Taxonomy File
+
+The `yago-taxonomy.ttl` file can be accessed and loaded in every process as follows:
+
+```python
+from rdflib import Graph
+
+taxonomy_graph = Graph()
+taxonomy_graph.parse('raw/yago-taxonomy.ttl', format='turtle') 
+```
+
+## Additional Information
+
+### Licensing
+
+The YAGO 4.5 dataset is available under the [Creative Commons Attribution-ShareAlike 3.0 license](https://creativecommons.org/licenses/by-sa/3.0/).
+
+### Citation
+
+If you use the YAGO 4.5 dataset in your work, please cite the
+following publication:
+
+```bibtex
+@article{suchanek2023integrating,
+  title={Integrating the Wikidata Taxonomy into YAGO},
+  author={Suchanek, Fabian M and Alam, Mehwish and Bonald, Thomas and Paris, Pierre-Henri and Soria, Jules},
+  journal={arXiv preprint arXiv:2308.11884},
+  year={2023}
+}
+```

README.md

@@ -1,99 +1,12 @@
-# YAGO 4.5 Dataset (English subset for LLM fine-tuning)
-
-## Dataset Description
-This datasets contains triples filtered from yago-facts.ttl and
-yago-beyond-wikipedia.ttl in the YAGO 4.5 dataset. The SPARQL query
-used to filter the triples is in `raw/filter.sparql`. This represents
-a subset of the YAGO 4.5 dataset maintaining only English labels. 
-
-I remapped some schema.org URIs to use the
-`http://yago-knowledge.org/resource/` which were not present in the
-schema.org vocabulary.  I also removed schema:sameAs and owl:sameAs
-relations from this dataset, as well as triples with xsd:anyURI object
-literals, as my goal is to use this dataset for fine-tuning a large
-language model for knowledge graph completion and I do not want
-to train the base model to predict these kind of relations.
-
-### Overview
-
-YAGO 4.5 is the latest version of the YAGO knowledge base. It is
-based on Wikidata — the largest public general-purpose knowledge
-base. YAGO refines the data as follows:
-
-* All entity identifiers and property identifiers are human-readable.
-* The top-level classes come from schema.org — a standard repertoire
-  of classes and properties maintained by Google and others. The lower
-  level classes are a careful selection of the Wikidata taxonomy.
-* The properties come from schema.org.
-* YAGO 4.5 contains semantic constraints in the form of SHACL. These
-  constraints keep the data clean, and allow for logical reasoning on
-  YAGO. 
-
-
-### Dataset Structure
-The dataset is structured as follows:
-
-- **raw/yago-taxonomy.ttl:** Contains the `rdfs:subClassOf` relations
-  for YAGO and the prefix mappings for the N-Triples.
-- **raw/facts.tar.gz:** Compressed file containing chunks of the
-  dataset in N-Triples format, representing the factual knowledge in
-  YAGO. 
-
-### Features
-
-Each RDF triple in the dataset is represented with the following features:
-
-- **subject:** The subject of the triple, representing the entity.
-- **predicate:** The predicate of the triple, representing the
-  relationship between the subject and object.
-- **object:** The object of the triple, representing the entity or
-  value linked by the predicate.
-
-### Splits
-
-The dataset is logically divided into multiple chunks, each containing
-a subset of RDF triples. Users can load specific chunks or the entire
-dataset based on their requirements.
-
-## Usage
-
-### Loading the Dataset
-
-The dataset can be loaded using the Hugging Face `datasets` library as follows:
-
-```python
-from datasets import load_dataset
-
-dataset = load_dataset('wikipunk/yago-4.5-en', num_proc=4)
-```
-
-### Accessing the YAGO Taxonomy File
-
-The `yago-taxonomy.ttl` file can be accessed and loaded in every process as follows:
-
-```python
-from rdflib import Graph
-
-taxonomy_graph = Graph()
-taxonomy_graph.parse('raw/yago-taxonomy.ttl', format='turtle') 
-```
-
-## Additional Information
-
-### Licensing
-
-The YAGO 4.5 dataset is available under the [Creative Commons Attribution-ShareAlike 3.0 license](https://creativecommons.org/licenses/by-sa/3.0/).
-
-### Citation
-
-If you use the YAGO 4.5 dataset in your work, please cite the
-following publication:
-
-```bibtex
-@article{suchanek2023integrating,
-  title={Integrating the Wikidata Taxonomy into YAGO},
-  author={Suchanek, Fabian M and Alam, Mehwish and Bonald, Thomas and Paris, Pierre-Henri and Soria, Jules},
-  journal={arXiv preprint arXiv:2308.11884},
-  year={2023}
-}
-```
+---
+dataset_info:
+  features:
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 17
+    num_examples: 1
+  download_size: 14
+  dataset_size: 17
+---

requirements.txt

@@ -0,0 +1 @@
+rdflib>=6.0.0

yago-4.5-en.py

@@ -1,7 +1,7 @@
 import os
 from datasets import DatasetBuilder, SplitGenerator, DownloadConfig, load_dataset, DownloadManager
 from rdflib import Graph, URIRef, Literal, BNode
-from rdflib.namespace import RDF, RDFS, OWL, XSD, Namespace
+from rdflib.namespace import RDF, RDFS, OWL, XSD, Namespace, NamespaceManager
 
 SCHEMA = Namespace('http://schema.org/')
 
@@ -10,7 +10,7 @@ YAGO = Namespace('http://yago-knowledge.org/resource/')
 class YAGO45DatasetBuilder(DatasetBuilder):
     VERSION = "1.0.0"
 
-    taxonomy = Graph()
+    taxonomy = Graph(bind_namespaces="core")
     
     def _info(self):
         # Define dataset metadata and features
@@ -47,7 +47,7 @@ class YAGO45DatasetBuilder(DatasetBuilder):
         # Load the chunks into an rdflib graph
         # Yield individual triples from the graph
         for chunk_path in chunk_paths:
-            graph = Graph()
+            graph = Graph(bind_namespaces="core")
             for prefix, namespace in prefix_mappings.items():
                 graph.bind(prefix, namespace)
             graph.parse(chunk_path, format='nt')
@@ -59,3 +59,5 @@ class YAGO45DatasetBuilder(DatasetBuilder):
                     'predicate': str(predicate),
                     'object': str(object_)
                 }
+
+