add script

yago-4.5-en.py

@@ -0,0 +1,61 @@
+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
+
+SCHEMA = Namespace('http://schema.org/')
+
+YAGO = Namespace('http://yago-knowledge.org/resource/')
+
+class YAGO45DatasetBuilder(DatasetBuilder):
+    VERSION = "1.0.0"
+
+    taxonomy = Graph()
+    
+    def _info(self):
+        # Define dataset metadata and features
+        return {
+            "features": {
+                "subject": "string",
+                "predicate": "string",
+                "object": "string"
+            },
+            "homepage": "https://yago-knowledge.org/",
+            "license": "CC BY 3.0",
+            "citation": "@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}}"
+        }
+    
+    def _split_generators(self, dl_manager):
+        # Download and extract the dataset
+        # Define splits for each chunk of your dataset.
+        
+        # Download and extract the dataset files
+        dl_manager.download_config = DownloadConfig(cache_dir=os.path.abspath("raw"))
+        dl_manager.download_and_extract(["raw/facts.tar.gz", "raw/yago-taxonomy.ttl"])
+        
+        # Load yago-taxonomy.ttl file in every process
+        self.taxonomy.parse(os.path.join(dl_manager.manual_dir, 'yago-taxonomy.ttl'), format='turtle')
+        
+        # Extract prefix mappings 
+        prefix_mappings = {prefix: namespace for prefix, namespace in self.taxonomy.namespaces()}
+        
+        # Define splits for each chunk
+        chunk_paths = [os.path.join(dl_manager.manual_dir, chunk) for chunk in os.listdir(dl_manager.manual_dir) if chunk.endswith('.nt')]
+        return [SplitGenerator(name="train", gen_kwargs={'chunk_paths': chunk_paths, 'prefix_mappings': prefix_mappings})]
+    
+    def _generate_examples(self, chunk_paths, prefix_mappings):
+        # Load the chunks into an rdflib graph
+        # Yield individual triples from the graph
+        for chunk_path in chunk_paths:
+            graph = Graph()
+            for prefix, namespace in prefix_mappings.items():
+                graph.bind(prefix, namespace)
+            graph.parse(chunk_path, format='nt')
+            
+            # Yield individual triples from the graph
+            for i, (subject, predicate, object_) in enumerate(graph):
+                yield i, {
+                    'subject': str(subject),
+                    'predicate': str(predicate),
+                    'object': str(object_)
+                }