compare with ogb-mag

README.md

@@ -140,13 +140,14 @@ Percentage of texts that would lose tokens at each candidate `seq_len`.
 On average we will have the following documents to tokens:
 
 
-| CDB | Docs | Tokens |
+| CDB | Domains | Tokens |
 |-------|------|--------|
 | Dec   |   43M   |   58B     |
 | Nov   |    39M  |    52B    |
 | Oct   |    33M  |     44B   |
-| **Total** | 115M | 115B|
-| **Total Unique** | 37M| 115B|
+| **Total** | 115M | 155B|
+| **Total Unique** | 37M| 155B|
+
 
 ## Text-Attributed Graph w/ Cleaning
 
@@ -154,8 +155,18 @@ On average we will have the following documents to tokens:
 Overall across CDB-Dec, CDB-Nov, CDB-Oct 
 
 
+
+
 # CDB v. OGB-MAG240M
 
+If we consider CDB across Dec, Nov, Oct as a static graph versus OGB-MAG240M (largest text-attributed graph dataset to-date.)
+
+
+
+| Dataset | Domains | Tokens |
+|-------|------|--------|
+| CDB   |   37M   |   155B     |
+| OGB-MAG240M   |  120M    |    30B    |