Recent research has taken advantage of Wikipedia's multilingualism as a
resource for cross-language information retrieval and machine translation, as
well as proposed techniques for enriching its cross-language structure. The
availability of documents in multiple languages also opens up new opportunities
for querying structured Wikipedia content, and in particular, to enable answers
that straddle different languages. As a step towards supporting such queries,
in this paper, we propose a method for identifying mappings between attributes
from infoboxes that come from pages in different languages. Our approach finds
mappings in a completely automated fashion. Because it does not require
training data, it is scalable: not only can it be used to find mappings between
many language pairs, but it is also effective for languages that are
under-represented and lack sufficient training samples. Another important
benefit of our approach is that it does not depend on syntactic similarity
between attribute names, and thus, it can be applied to language pairs that
have distinct morphologies. We have performed an extensive experimental
evaluation using a corpus consisting of pages in Portuguese, Vietnamese, and
English. The results show that not only does our approach obtain high precision
and recall, but it also outperforms state-of-the-art techniques. We also
present a case study which demonstrates that the multilingual mappings we
derive lead to substantial improvements in answer quality and coverage for
structured queries over Wikipedia content.

本文提出了一个方法，用于在不同语言的 Infoboxes 之间识别属性映射，该方法具有可扩展性和适用性广泛性，它能够通过 Wikipedia 的多语言资源和跨语言结构支持 Wikipedia 内容的结构化查询，并提高了查询结果的质量和覆盖范围。