"""Create reasoning_engine
Generated by Phi-Octopus Eden
2025-11-07 08:21:55.176334
"""

```python
from typing import Dict, List, Tuple


class KnowledgeBase:
    def __init__(self):
        self.knowledge = {}

    def add_fact(self, fact: str) -> None:
        """Add a new fact to the knowledge base."""
        if fact not in self.knowledge:
            self.knowledge[fact] = []

    def query(self, question: str) -> List[str]:
        """Query the knowledge base for relevant facts."""
        return [fact for fact in self.knowledge.keys() if question in fact]


class ReasoningEngine:
    def __init__(self, kb: KnowledgeBase):
        self.kb = kb

    def infer(self, premises: List[str]) -> List[Tuple[str, bool]]:
        """
        Infer conclusions from the given premises.
        
        :param premises: A list of known facts to be used in inference.
        :return: A list of tuples containing inferred facts and their truth values.
        """
        inferred_facts = []
        for premise in premises:
            relevant_facts = self.kb.query(premise)
            if relevant_facts:
                for fact in relevant_facts:
                    # Simple inference rule: If a fact matches the premise, it is true
                    truth_value = True  # Simplified logic; real world would need more complex rules
                    inferred_facts.append((fact, truth_value))
        return inferred_facts


# Example usage:

kb = KnowledgeBase()
kb.add_fact("The cat is on the mat.")
kb.add_fact("If the cat is on the mat, then it is sleeping.")

engine = ReasoningEngine(kb)
premises = ["The cat is on the mat."]
inferences = engine.infer(premises)

for inference in inferences:
    print(f"Inferred: {inference[0]} -> {'True' if inference[1] else 'False'}")
```

This example creates a simple reasoning engine that can infer conclusions from given premises and a knowledge base. It uses basic rules for inference, which would need to be expanded with more complex logic in practical applications.