### Body

The _trigger_ log doesn't show that a trigger timed out when it is canceled due to timeout.

We should try to see if we can add a log message that would show up in the right place.  If we emit it from the trigger process, it might show up out of order.  

But then again, if we ultimately don't need to go back to the task, that would not be a problem.  

Additionally if we ultimately can "log from anywhere" then again, this would provide a clean solution.

This came up in PR discussion here: https://github.com/apache/airflow/pull/30853#discussion_r1187018026

The relevant trigger code is here: https://github.com/apache/airflow/blob/main/airflow/jobs/triggerer_job_runner.py#L598-L619

I think we could add logic so that when we receive a cancelled error (which could be for a few different reasons) then we can log the reason for the cancellation.   I think we could just add an `except CancelledError` and then log the reason.  We might need also to update the code in the location where we actually _initiate_ the cancellation to add sufficient information for the log message.

cc @syedahsn @phanikumv @jedcunningham @pankajastro 

### Committer

- [X] I acknowledge that I am a maintainer/committer of the Apache Airflow project.
job_runner.load_triggers()
        
        for _ in range(30):
            if not job_runner.trigger_runner.triggers:
                break
            time.sleep(0.1)
        else:
            pytest.fail("TriggerRunner never deleted trigger")
    finally:
        
        job_runner.trigger_runner.stop = True
def test_trigger_create_race_condition_18392(session, tmp_path):
    """
    This verifies the resolution of race condition documented in github issue #18392.
    Triggers are queued for creation by TriggerJob.load_triggers.
    There was a race condition where multiple triggers would be created unnecessarily.
    What happens is the runner completes the trigger and purges from the "running" list.
    Then job.load_triggers is called and it looks like the trigger is not running but should,
    so it queues it again.
    The scenario is as follows:
        1. job.load_triggers (trigger now queued)
        2. runner.create_triggers (trigger now running)
        3. job.handle_events (trigger still appears running so state not updated in DB)
        4. runner.cleanup_finished_triggers (trigger completed at this point; trigger from "running" set)
        5. job.load_triggers (trigger not running, but also not purged from DB, so it is queued again)
        6. runner.create_triggers (trigger created again)
    This test verifies that under this scenario only one trigger is created.
    """
    path = tmp_path / "test_trigger_bad_respawn.txt"
    class TriggerRunner_(TriggerRunner):