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class WinobiasReader(DatasetReader):
 | def __init__(
 |     self,
 |     max_span_width: int,
 |     token_indexers: Dict[str, TokenIndexer] = None,
 |     **kwargs
 | ) -> None

A dataset reader for the dataset described in Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods

Winobias is a dataset to analyse the issue of gender bias in co-reference resolution. It contains simple sentences with pro/anti stereotypical gender associations with which to measure the bias of a coreference system trained on another corpus. It is effectively a toy dataset and as such, uses very simplistic language; it has little use outside of evaluating a model for bias.

The dataset is formatted with a single sentence per line, with a maximum of 2 non-nested coreference clusters annotated using either square or round brackets. For example:

[The salesperson] sold (some books) to the librarian because [she] was trying to sell (them).

Returns a list of Instances which have four fields : text, a TextField containing the full sentence text, spans, a ListField[SpanField] of inclusive start and end indices for span candidates, and metadata, a MetadataField that stores the instance's original text. For data with gold cluster labels, we also include the original clusters (a list of list of index pairs) and a SequenceLabelField of cluster ids for every span candidate in the metadata also.


  • max_span_width : int
    The maximum width of candidate spans to consider.
  • token_indexers : Dict[str, TokenIndexer], optional
    This is used to index the words in the sentence. See TokenIndexer. Default is {"tokens": SingleIdTokenIndexer()}.


class WinobiasReader(DatasetReader):
 | ...
 | def text_to_instance(
 |     self,
 |     sentence: List[Token],
 |     gold_clusters: Optional[List[List[Tuple[int, int]]]] = None
 | ) -> Instance


  • sentence : List[Token]
    The already tokenised sentence to analyse.
  • gold_clusters : Optional[List[List[Tuple[int, int]]]], optional (default = None)
    A list of all clusters in the sentence, represented as word spans. Each cluster contains some number of spans, which can be nested and overlap, but will never exactly match between clusters.


  • An Instance containing the following Fields:
    text : TextField The text of the full sentence. spans : ListField[SpanField] A ListField containing the spans represented as SpanFields with respect to the sentence text. span_labels : SequenceLabelField, optional The id of the cluster which each possible span belongs to, or -1 if it does not belong to a cluster. As these labels have variable length (it depends on how many spans we are considering), we represent this a as a SequenceLabelField with respect to the spans ListField.