Open information extraction (OIE) systems extract relations and their
arguments from natural language text in an unsupervised manner. The resulting
extractions are a valuable resource for downstream tasks such as knowledge base
construction, open question answering, or event schema induction. In this
paper, we release, describe, and analyze an OIE corpus called OPIEC, which was
extracted from the text of English Wikipedia. OPIEC complements the available
OIE resources: It is the largest OIE corpus publicly available to date (over
340M triples) and contains valuable metadata such as provenance information,
confidence scores, linguistic annotations, and semantic annotations including
spatial and temporal information. We analyze the OPIEC corpus by comparing its
content with knowledge bases such as DBpedia or YAGO, which are also based on
Wikipedia. We found that most of the facts between entities present in OPIEC
cannot be found in DBpedia and/or YAGO, that OIE facts often differ in the
level of specificity compared to knowledge base facts, and that OIE open
relations are generally highly polysemous. We believe that the OPIEC corpus is
a valuable resource for future research on automated knowledge base
construction.

本文释放、描述和分析了一个名为 OPIEC 的 OIE 语料库，其中包含超过 340M 个三元组，是目前公开可用的最大的 OIE 语料库。我们发现，在 OPIEC 中存在的大多数实体之间的事实在 DBpedia 和 / 或 YAGO 中找不到。此外，OIE open relations 通常高度多义性。我们相信 OPIEC 语料库是未来自动知识库构建研究的有价值的资源。