Update README.md

README.md

@@ -40,6 +40,32 @@ TL;DR: The datasets for the temporal knowledge graph reasoning task.
  'args': ['e1', 'r1', 't1']}
 ```
 
+'args' is the argument list of the query function, where name starting with 'e' is entity, and 'r' for relation, 't' for timestamp.
+
+assert len(query) == len(args)
+
+In order to decode query ids into text, we should use a vocabulary (i.e. entity2idx, relation2idx and timestamp2idx).
+Therefore, we use the code below to load meta info which contains the vocabulary:
+
+```python
+>>> dataset = load_dataset("linxy/ICEWS14", "meta")
+>>> meta_info = dataset_meta["train"][0]
+>>> meta_info
+{'dataset': 'ICEWS14',
+ 'entity_count': 7128,
+ 'relation_count': 230,
+ 'timestamp_count': 365,
+ 'valid_triples_count': 8941,
+ 'test_triples_count': 8963,
+ 'train_triples_count': 72826,
+ 'triple_count': 90730,
+ 'query_meta': {'query_name': [...], 'queries_count': [...], 'avg_answers_count': [...], ...},
+ 'entity2idx': {'name': [...], 'id': [...]},
+ 'relation2idx': {'name': [...], 'id': [...]},
+ 'timestamp2idx': {'name': [...], 'id': [...]},
+```
+
+
 <details>
   <summary>👈 🔎 Dataset statistics: queries_count</summary>
 
@@ -138,6 +164,9 @@ TL;DR: The datasets for the temporal knowledge graph reasoning task.
 
 <br/>
 
+## ✉️ Contact
+
+- Lin Xueyuan: [email protected]
 
 ## 🤝 Citation