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TAGS_TO_SPANS_FUNCTION_TYPE = Callable[[List[str], Optional[List[str]]], List[TypedStringSpan]]

SpanBasedF1Measure Objects#

class SpanBasedF1Measure(Metric):
 | def __init__(
 |     self,
 |     vocabulary: Vocabulary,
 |     tag_namespace: str = "tags",
 |     ignore_classes: List[str] = None,
 |     label_encoding: Optional[str] = "BIO",
 |     tags_to_spans_function: Optional[TAGS_TO_SPANS_FUNCTION_TYPE] = None
 | ) -> None

The Conll SRL metrics are based on exact span matching. This metric implements span-based precision and recall metrics for a BIO tagging scheme. It will produce precision, recall and F1 measures per tag, as well as overall statistics. Note that the implementation of this metric is not exactly the same as the perl script used to evaluate the CONLL 2005 data - particularly, it does not consider continuations or reference spans as constituents of the original span. However, it is a close proxy, which can be helpful for judging model performance during training. This metric works properly when the spans are unlabeled (i.e., your labels are simply "B", "I", "O" if using the "BIO" label encoding).


 | def get_metric(self, reset: bool = False)


  • Dict[str, float]
    A Dict per label containing following the span based metrics:

    • precision : float
    • recall : float
    • f1-measure : float

    Additionally, an overall key is included, which provides the precision, recall and f1-measure for all spans.


 | def reset(self)