Although several datasets annotated for anaphoric reference/coreference
exist, even the largest such datasets have limitations in terms of size, range
of domains, coverage of anaphoric phenomena, and size of documents included.
Yet, the approaches proposed to scale up anaphoric annotation haven't so far
resulted in datasets overcoming these limitations. In this paper, we introduce
a new release of a corpus for anaphoric reference labelled via a
game-with-a-purpose. This new release is comparable in size to the largest
existing corpora for anaphoric reference due in part to substantial activity by
the players, in part thanks to the use of a new resolve-and-aggregate paradigm
to 'complete' markable annotations through the combination of an anaphoric
resolver and an aggregation method for anaphoric reference. The proposed method
could be adopted to greatly speed up annotation time in other projects
involving games-with-a-purpose. In addition, the corpus covers genres for which
no comparable size datasets exist (Fiction and Wikipedia); it covers singletons
and non-referring expressions; and it includes a substantial number of long
documents (> 2K in length).

通过玩游戏来标注语料库是一种有效的方法，本文提出了一种用于指代和共识关系的语料库，相对于先前发布的语料库，它具有更广泛的领域、更多的标记、更长的文档和更高的标注速度。