  We present a dataset of manually annotated relationships between characters
in literary texts, in order to support the training and evaluation of automatic
methods for relation type prediction in this domain (Makazhanov et al., 2014;
Kokkinakis, 2013) and the broader computational analysis of literary character
(Elson et al., 2010; Bamman et al., 2014; Vala et al., 2015; Flekova and
Gurevych, 2015). In this work, we solicit annotations from workers on Amazon
Mechanical Turk for 109 texts ranging from Homer's _Iliad_ to Joyce's _Ulysses_
on four dimensions of interest: for a given pair of characters, we collect
judgments as to the coarse-grained category (professional, social, familial),
fine-grained category (friend, lover, parent, rival, employer), and affinity
(positive, negative, neutral) that describes their primary relationship in a
text. We do not assume that this relationship is static; we also collect
judgments as to whether it changes at any point in the course of the text.
