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    • Token Distribution across Person

    The following histogram captures the token distribution per different part-of-speech (POS) tags.

    Legend on the top-right shows the different values the Person attribute takes.
    'NA' denotes those tokens which do not possess the Person attribute.

    Person

    Token examples for each POS:

     NOUN       PUNCT       ADV       VERB       PRON       AUX       ADJ       CCONJ       SCONJ       DET       PROPN       ADP       NUM       INTJ       SYM       X      

    Person agreement rules:

    The following decision tree visualizes the rules used for classifying presence/absence of morphological agreement between two tokens that are connected by a dependency relation denoted by relation. head-pos and child-pos refer to the POS tag of the head and child token respectively.

    Each node of the tree represents a portion of the data. samples denotes the number of training data points in that node. value is the class distribution within that node. Each edge denotes the feature used for splitting.
    Leaf nodes contain the description of all of the features that appear in that leaf. * denotes that the feature can take any value.

    Tree for p=0.01

    Click on to show summary of agreement rules.

    1. VERB tokens agree with their dependent tokens for the dependency relations: subject(subj)

    2. VERB tokens agree when the dependent token belongs to [VERB] for the dependency relations: conjunct(conj)

    3. AUX tokens agree when the dependent token belongs to [VERB] for the dependency relations: parataxis(parataxis), subject(subj@cop)

    4. AUX tokens agree when the dependent token belongs to [AUX, VERB] for the dependency relations: modifer(mod)

    Person

    Examples for each leaf node:

     Leaf-0       Leaf-1       Leaf-2       Leaf-3       Leaf-4       Leaf-5       Leaf-6       Leaf-7       Leaf-8      

    Click on to expand the tree.