### 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)

continue
            if not isinstance(dag.timetable, DatasetTriggeredTimetable):
                self.log.error(
                    "DAG '%s' was dataset-scheduled, but didn't have a DatasetTriggeredTimetable!",
                    dag_model.dag_id,
                )
                continue
            dag_hash = self.dagbag.dags_hash.get(dag.dag_id)
            
            
            
            
            
            
            
            
            exec_date = exec_dates[dag.dag_id]
            if (dag.dag_id, exec_date) not in existing_dagruns:
                previous_dag_run = session.scalar(
                    select(DagRun)
                    .where(
                        DagRun.dag_id == dag.dag_id,
                        DagRun.execution_date < exec_date,
                        DagRun.run_type == DagRunType.DATASET_TRIGGERED,
                    )
                    .order_by(DagRun.execution_date.desc())
                    .limit(1)
                )
                dataset_event_filters = [
                    DagScheduleDatasetReference.dag_id == dag.dag_id,