test_time_scaling/knowledge_level_test.py

# from nltk.corpus import wordnet as wn

# # 你想查询的数学术语列表
# math_terms = ["ideal"]

# for term in math_terms:
#     print(f"\nTerm: {term}")
#     synsets = wn.synsets(term, pos=wn.NOUN)
#     if not synsets:
#         print("  No synsets found.")
#     for syn in synsets:
#         print(f"  Synset: {syn.name()}, Definition: {syn.definition()}, Depth: {syn.min_depth()}")

from SPARQLWrapper import SPARQLWrapper, JSON
import requests

def get_superclasses(entity_id):
    sparql = SPARQLWrapper("https://query.wikidata.org/sparql")
    query = f"""
    SELECT ?super ?superLabel WHERE {{
      wd:{entity_id} wdt:P279* ?super .
      SERVICE wikibase:label {{ bd:serviceParam wikibase:language "en". }}
    }}
    """
    sparql.setQuery(query)
    sparql.setReturnFormat(JSON)
    results = sparql.query().convert()
    return [(r["super"]["value"], r["superLabel"]["value"]) for r in results["results"]["bindings"]]

def get_wikidata_id(term):
    url = f"https://www.wikidata.org/w/api.php"
    params = {
        'action': 'wbsearchentities',
        'language': 'en',
        'format': 'json',
        'search': term
    }
    response = requests.get(url, params=params)
    return response.json()['search'][0]['id']

def print_superclasses_for_term(term):
    entity_id = get_wikidata_id(term)
    print(f"{term} -> Wikidata ID: {entity_id}")
    results = get_superclasses(entity_id)
    print(f"Superclasses for {term}:")
    for uri, label in results:
        print(label)

# 示例：查询"Entropy"的super classes
# print_superclasses_for_term("Entropy")

for term in ["group","Entropy", "Matrix", "Integration"]:
    print_superclasses_for_term(term)
    print("-" * 30)