Update README.md

README.md

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----
-license: cc-by-4.0
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+---
+license: cc-by-4.0
+---
+
+# Clean ConceptNet Data for All Languages
+
+## Data Details
+
+For our project on [Retrofitting Glove embeddings for Low Resource Languages](https://github.com/pyRis/retrofitting-embeddings-lrls/tree/main?tab=readme-ov-file), we extracted all data from the [ConceptNet](https://github.com/commonsense/conceptnet5/wiki/Downloads) database for 304 languages. The extraction process involved several steps to clean and analyze the data from the official ConceptNet dump available [here](https://s3.amazonaws.com/conceptnet/downloads/2019/edges/conceptnet-assertions-5.7.0.csv.gz).
+
+The final extracted dataset is a JSON file representing a dictionary with language codes and start and end edges for each language. Start edges represent the unique words in a target language, while end edges are the words related to the start edges through various types of relationships. The relationship types and sources are not extracted.
+
+### Dataset Structure
+
+cn_relations_clean.json:
+
+``
+{
+'language_iso_code_1':{'start_edge_word_1':['end_edge_word_1', 'end_edge_word_2', ...], ...},
+...
+}
+``
+
+### Licensing Information
+
+This work includes data from ConceptNet 5, which was compiled by the
+Commonsense Computing Initiative. ConceptNet 5 is freely available under
+the Creative Commons Attribution-ShareAlike license (CC BY SA 3.0) from
+http://conceptnet.io.
+
+### Citation Information
+
+```
+@paper{speer2017conceptnet,
+    author = {Robyn Speer and Joshua Chin and Catherine Havasi},
+    title = {ConceptNet 5.5: An Open Multilingual Graph of General Knowledge},
+    conference = {AAAI Conference on Artificial Intelligence},
+    year = {2017},
+    pages = {4444--4451},
+    keywords = {ConceptNet; knowledge graph; word embeddings},
+    url = {http://aaai.org/ocs/index.php/AAAI/AAAI17/paper/view/14972}
+}
+```