  Relation extraction aims to identify the target relations of entities in
texts. Relation extraction is very important for knowledge base construction
and text understanding. Traditional binary relation extraction, including
supervised, semi-supervised and distant supervised ones, has been extensively
studied and significant results are achieved. In recent years, many complex
relation extraction tasks, i.e., the variants of simple binary relation
extraction, are proposed to meet the complex applications in practice. However,
there is no literature to fully investigate and summarize these complex
relation extraction works so far. In this paper, we first report the recent
progress in traditional simple binary relation extraction. Then we summarize
the existing complex relation extraction tasks and present the definition,
recent progress, challenges and opportunities for each task.
