### What do you see as an issue?

The documentation for zombie tasks https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/tasks.html#zombie-undead-tasks is a bit abstract at the moment. There is a scope for enhancing the document by explaining how Airflow detects tasks as zombies

### Solving the problem

We can enhance the documentation by translating this query https://github.com/astronomer/airflow/blob/main/airflow/jobs/scheduler_job_runner.py#L1721 to a layman readable text in our documentation.

### Anything else

It might also help to add developer contribution steps to reproduce zombies locally.

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

self,
        dag_models: Collection[DagModel],
        dataset_triggered_dag_info: dict[str, tuple[datetime, datetime]],
        session: Session,
    ) -> None:
        """For DAGs that are triggered by datasets, create dag runs."""
        
        
        
        
        exec_dates = {
            dag_id: timezone.coerce_datetime(last_time)
            for dag_id, (_, last_time) in dataset_triggered_dag_info.items()
        }
        existing_dagruns: set[tuple[str, timezone.DateTime]] = set(
            session.execute(
                select(DagRun.dag_id, DagRun.execution_date).where(
                    tuple_in_condition((DagRun.dag_id, DagRun.execution_date), exec_dates.items())
                )
            )
        )
        for dag_model in dag_models:
            dag = self.dagbag.get_dag(dag_model.dag_id, session=session)
            if not dag:
                self.log.error("DAG '%s' not found in serialized_dag table", dag_model.dag_id)