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@ -60,6 +60,7 @@ DEFAULT_MODEL = Config().from_str(default_config)["model"]
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DEFAULT_CLUSTERS_PREFIX = "coref_clusters"
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@Language.factory(
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"coref",
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assigns=["doc.spans"],
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@ -389,6 +390,7 @@ class CoreferenceResolver(TrainablePipe):
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out[fname] = mean([ss[fname] for ss in scores])
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return out
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class SpanPredictor(TrainablePipe):
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"""Pipeline component to resolve one-token spans to full spans.
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@ -475,4 +477,3 @@ class SpanPredictor(TrainablePipe):
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def score(self, examples, **kwargs):
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# TODO this will overlap significantly with coref, maybe factor into function
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...
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