init

data/t_rex.filter_unified.jsonl

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-size 408499494

data/t_rex.filter_unified.min_entity_5.jsonl

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-size 51784028
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+size 1680622480

data/t_rex.filter_unified.min_entity_5.train.jsonl

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 version https://git-lfs.github.com/spec/v1
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+size 1317139435

data/t_rex.filter_unified.min_entity_5.validation.jsonl

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stats.py

@@ -1,37 +0,0 @@
-from itertools import product
-import pandas as pd
-from datasets import load_dataset
-
-
-def get_stats(name):
-    relation = []
-    size = []
-    data = load_dataset("relbert/t_rex", name)
-    splits = data.keys()
-    for split in splits:
-        df = data[split].to_pandas()
-        size.append({
-            "number of pairs": len(df),
-            "number of unique relation types": len(df["relation"].unique())
-        })
-        relation.append(df.groupby('relation')['head'].count().to_dict())
-    relation = pd.DataFrame(relation, index=[f"number of pairs ({s})" for s in splits]).T
-    relation = relation.fillna(0).astype(int)
-    size = pd.DataFrame(size, index=splits).T
-    return relation, size
-
-df_relation, df_size = get_stats("filter_unified.min_entity_4_max_predicate_10")
-print(f"\n- Number of instances (`filter_unified.min_entity_4_max_predicate_10`) \n\n {df_size.to_markdown()}")
-print(f"\n- Number of pairs in each relation type (`filter_unified.min_entity_4_max_predicate_10`) \n\n {df_relation.to_markdown()}")
-
-
-parameters_min_e_freq = [1, 2, 3, 4]
-parameters_max_p_freq = [100, 50, 25, 10]
-df_size_list = []
-for e, p in product(parameters_min_e_freq, parameters_max_p_freq):
-    _, df_size = get_stats(f"filter_unified.min_entity_{e}_max_predicate_{p}")
-    df_size.pop("test")
-    df_size.columns = [f"min_entity_{e}_max_predicate_{p} ({c})" for c in df_size.columns]
-    df_size_list.append(df_size)
-df_size_list = pd.concat([i.T for i in df_size_list])
-print(df_size_list.to_markdown())