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@@ -12,4 +12,4 @@ Coreference annotation is a critical task for much research in the digital human
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  The model takes as input plain sentences (e.g. `"'The visitor sat and listened to her retreating feet."`), and returns the sentence with inline coreference annotations (e.g. `"[The visitor: 1] sat and listened to [her: 2] retreating feet."`).
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- For an example of how to use the model, see this tutorial on Google Colab or look at `the get_annotations.py` file under the **Files and versions** tab above. If you want to convert the annotated sentences into coreference clusters, the `get_ent_clusters.py` script also under the **Files and versions** tab will output clusters of the form `{1: ['The visitor|0'], 2: ['her|6']}` where the keys are the cluster indices and each value is a list of entities in that cluster. Each entity consists of the representative substring and the index of the first word in the substring combined with a pipe.
 
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  The model takes as input plain sentences (e.g. `"'The visitor sat and listened to her retreating feet."`), and returns the sentence with inline coreference annotations (e.g. `"[The visitor: 1] sat and listened to [her: 2] retreating feet."`).
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+ For an example of how to use the model, see [this tutorial on Google Colab](https://colab.research.google.com/drive/1G7ziZvFo_sZoygxlS2Nyt_CejRs0r9Jw?usp=sharing) or look at `the get_annotations.py` file under the **Files and versions** tab above. If you want to convert the annotated sentences into coreference clusters, the `get_ent_clusters.py` script also under the **Files and versions** tab will output clusters of the form `{1: ['The visitor|0'], 2: ['her|6']}` where the keys are the cluster indices and each value is a list of entities in that cluster. Each entity consists of the representative substring and the index of the first word in the substring combined with a pipe.