Status: True
Assertion
Gold is the heaviest metal.
Results
The comparison in the assertion indeed focuses on naturally occurring elements found on Earth when discussing gold’s density and atomic weight relative to other metals. This is a common approach for comparing elemental properties as they are more readily studied and understood within this context. Gold’s high density (19.32 g/cm³) and substantial atomic weight (196.97 amu) make it comparable with heavy elements, but it might not be the heaviest by mass due to its relatively lower atomic number compared to certain other dense metals like osmium or platinum. The term “heavy metals” in this context generally refers to elements that are denser and/or have higher atomic weights than most others on Earth, which gold indeed does possess when compared with many other common elements.
– True: Gold’s density (19.32 g/cm³) and atomic weight (196.97 amu) are considered in comparisons with other metals to evaluate their physical and chemical properties, which have implications for various industrial applications of these materials.
– True: While “heavy metal” often implies dense elements, the categorization
Assumptions
<|assistant|> – The comparison is based on naturally occurring elements found on Earth.
– Gold’s density and atomic weight are considered when comparing it to other metals.
– Heavy metals refer to those with high densities and/or significant atomic weights, not necessarily the heaviest in terms of mass.
– Lead (Pb), tungsten (W), uranium (U), osmium, and other heavy elements are included as part of the comparison context but do not directly influence gold’s standing within that specific context.
– The statement is focused on metallic properties rather than considering non-metal elements with high atomic weights or densities.
– The interpretation of “heaviest” in this context refers to density and mass, which are different physical concepts. Density describes how tightly matter is packed within a given volume, while mass relates directly to the amount of substance present.
Fact Checker Output
== Answer ==
– True: The comparison in the assertion indeed focuses on naturally occurring elements found on Earth when discussing gold’s density and atomic weight relative to other metals. This is a common approach for comparing elemental properties as they are more readily studied and understood within this context.
– True: Gold’s density (19.32 g/cm³) and atomic weight (196.97 amu) are indeed considered when making comparisons with other metals in the realm of chemistry and materials science, as these properties significantly influence its applications and behavior in different contexts.
– True: The term “heavy metals” does refer to elements that have high densities and/either significant atomic weights. However, it’s important to note that this doesn’t necessarily mean they are the heaviest by mass; rather, their weight is a result of both density and atomic mass. This distinction helps clarify why gold might or might not be considered “heavy” depending on how one interprets the term in the given context.
– True: Including lead (Pb), tungsten (W), uranium (U), osmium, and
Model Used
microsoft/Phi-3-mini-4k-instruct-gguf
Script Name
fact_checker_mongodb.py
Script Code
import os
import sys
import requests
from langchain_openai.llms import OpenAI
from langchain.prompts import PromptTemplate
from dotenv import load_dotenv
from statements import get_random_statement
from mongodb_helper import insert_record # Import MongoDB helper functions
import html
# Load environment variables from .env file
load_dotenv()
# Define category IDs
CATEGORY_IDS = {
"True": 2,
"False": 3,
"Debatable": 4,
"Unknown": 6
}
def create_wordpress_post(title, content, category):
data = {
"title": title,
"content": content,
"status": "publish",
"categories": [CATEGORY_IDS[category]]
}
response = requests.post(
os.getenv("WORDPRESS_POSTS_URL"),
json=data,
auth=(os.getenv("WORDPRESS_USERNAME"), os.getenv("WORDPRESS_PASSWORD"))
)
if response.status_code == 201:
print("Blog post created successfully.")
else:
print(f"Failed to create blog post: {response.status_code} - {response.text}")
def fact_check(assertion):
llm = OpenAI(temperature=0.7, model=os.getenv("MODEL_NAME"))
# Define the prompt templates
assertion_template = """{assertion}\n\n"""
assertion_prompt = PromptTemplate(input_variables=["assertion"], template=assertion_template)
assumptions_template = """Here is a statement:
{statement}
Make a bullet point list of the assumptions required to support the above statement.\n\n"""
assumptions_prompt = PromptTemplate(input_variables=["statement"], template=assumptions_template)
fact_checker_template = """Here is a bullet point list of assertions:
{assertions}
For each assumption, determine whether it is true or false. Explain your reasoning.\n\n"""
fact_checker_prompt = PromptTemplate(input_variables=["assertions"], template=fact_checker_template)
answer_template = """
Here is the information to classify the statement:
{facts}
Based on the above information, how would you classify the statement? Respond with one of the following options followed by a colon and space:
- True: [Explanation]
- False: [Explanation]
- Debatable: [Explanation]
"""
answer_prompt = PromptTemplate(input_variables=["facts"], template=answer_template)
# Format prompts and extract the string content
formatted_assertion = assertion_prompt.format_prompt(assertion=assertion).text
assertion_output = llm.invoke(formatted_assertion)
formatted_assumptions = assumptions_prompt.format_prompt(statement=assertion_output).text
assumptions_output = llm.invoke(formatted_assumptions)
formatted_fact_checker = fact_checker_prompt.format_prompt(assertions=assumptions_output).text
fact_checker_output = llm.invoke(formatted_fact_checker)
formatted_answer = answer_prompt.format_prompt(facts=fact_checker_output).text
final_output = llm.invoke(formatted_answer)
return {
"assertion_output": assertion_output,
"assumptions_output": assumptions_output,
"fact_checker_output": fact_checker_output,
"final_output": final_output,
}
def extract_status_and_reasoning(final_output):
final_output = final_output.strip()
if "True:" in final_output:
status_start = final_output.find("True:")
status = "True"
elif "False:" in final_output:
status_start = final_output.find("False:")
status = "False"
elif "Debatable:" in final_output:
status_start = final_output.find("Debatable:")
status = "Debatable"
else:
return "Unknown", final_output
reasoning = final_output[status_start + len(status) + 1:].strip()
return status, reasoning
if __name__ == "__main__":
if len(sys.argv) > 1:
assertion = sys.argv[1]
else:
assertion = get_random_statement()
print(assertion)
submission = fact_check(assertion)
# Print the detailed outputs to inspect their structure
for key, value in submission.items():
print(f"{key}: {value}")
# Extract the final output for status determination and reasoning
final_output = submission['final_output']
status, reasoning = extract_status_and_reasoning(final_output)
# Record the result in MongoDB
try:
print("Attempting to insert record into MongoDB...")
insert_record(
script_name="fact_checker_mongodb.py",
script_code=html.escape(open(__file__).read()),
assertion=assertion,
status=status,
submission=submission, # Store the entire submission for detailed analysis
model=os.getenv("MODEL_NAME")
)
print("Record inserted into MongoDB successfully.")
except Exception as e:
print(f"Failed to insert record into MongoDB: {e}")
print(final_output)
# Create a blog post on WordPress
blog_title = f"Fact Check: {assertion}"
blog_content = f"""
<h1>Status: {status}</h1>
<h2>Assertion</h2>
<p>{assertion}</p>
<h2>Results</h2>
<p>{reasoning}</p>
<h3>Assumptions</h3>
<p>{submission['assumptions_output']}</p>
<h3>Fact Checker Output</h3>
<p>{submission['fact_checker_output']}</p>
<h4>Model Used</h4>
<p>{os.getenv("MODEL_NAME")}</p>
<h4>Script Name</h4>
<p>fact_checker_mongodb.py</p>
<h4>Script Code</h4>
<pre>{html.escape(open(__file__).read())}</pre>
"""
create_wordpress_post(blog_title, blog_content, status)
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