Entity linking is an indispensable operation of populating knowledge
repositories for information extraction. It studies on aligning a textual
entity mention to its corresponding disambiguated entry in a knowledge
repository. In this paper, we propose a new paradigm named distantly supervised
entity linking (DSEL), in the sense that the disambiguated entities that belong
to a huge knowledge repository (Freebase) are automatically aligned to the
corresponding descriptive webpages (Wiki pages). In this way, a large scale of
weakly labeled data can be generated without manual annotation and fed to a
classifier for linking more newly discovered entities. Compared with
traditional paradigms based on solo knowledge base, DSEL benefits more via
jointly leveraging the respective advantages of Freebase and Wikipedia.
Specifically, the proposed paradigm facilitates bridging the disambiguated
labels (Freebase) of entities and their textual descriptions (Wikipedia) for
Web-scale entities. Experiments conducted on a dataset of 140,000 items and
60,000 features achieve a baseline F1-measure of 0.517. Furthermore, we analyze
the feature performance and improve the F1-measure to 0.545.

本文提出了一种名为遥感监督实体链接 (DSEL) 的新模式，它利用 Freebase 和 Wikipedia 的各自优势，桥接实体的已消除的标签 (Freebase) 和它们的文本描述 (Wikipedia)，自动对齐大量的弱标注数据，并将其提供给分类器来链接新发现的实体，实验结果表明，在一个由 140,000 个条目和 60,000 个特征组成的数据集上，基线 F1 值为 0.517，而经过改进后可以达到 0.545。