fix readme

check_stats.py

@@ -8,6 +8,8 @@ parameters_min_e_freq = [1, 2, 3, 4]
 parameters_max_p_freq = [100, 50, 25, 10]
 
 stats = []
+predicate = {}
+
 for min_e_freq, max_p_freq in product(parameters_min_e_freq, parameters_max_p_freq):
 
     with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.train.jsonl") as f:
@@ -21,6 +23,7 @@ for min_e_freq, max_p_freq in product(parameters_min_e_freq, parameters_max_p_fr
     with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.jsonl") as f:
         full = [json.loads(i) for i in f.read().split('\n') if len(i) > 0]
         df_full = pd.DataFrame(full)
+        predicate[f"min_entity_{min_e_freq}_max_predicate_{max_p_freq}"] = df_full['predicate'].unique().tolist()
 
     stats.append({
         "data": f"filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}",
@@ -48,6 +51,7 @@ print(df.to_markdown())
 with open(f"data/t_rex.filter_unified.test.jsonl") as f:
     test = [json.loads(i) for i in f.read().split('\n') if len(i) > 0]
     df_test = pd.DataFrame(test)
+    predicate["test"] = df_test['predicate'].unique().tolist()
 df_test = pd.DataFrame([{
     "number of triples (test)": len(df_test),
     "number of unique predicates (test)": len(df_test['predicate'].unique()),
@@ -55,6 +59,7 @@ df_test = pd.DataFrame([{
             list(set(df_test['object'].unique().tolist() + df_test['subject'].unique().tolist()))
     )
 }])
+
 for c in df_test.columns:
     df_test.loc[:, c] = df_test[c].map('{:,d}'.format)
 print(df_test.to_markdown(index=False))
@@ -66,3 +71,7 @@ df.pop("number of unique predicates (all)")
 df.pop("number of unique entities (all)")
 df = df[sorted(df.columns)]
 df.to_csv("data/stats.csv")
+
+# predicates in training vs test
+with open("data/predicates.json", "w") as f:
+    json.dump(predicate, f)