Relation extraction (RE) is a promising way to extend the semantic web from web pages. However, it is unclear how RE can deal with the several challenges of web pages such as noise, data sparsity and conflicting information. In this paper, we benchmark state-of-the-art RE approaches on the particular case of company web pages, since company web pages are important source of information for Fin-tech and BusinnessTech. To this end, we present a method to build a corpus mimicking web pages characteristics. This corpus was used to evaluate several deep learning RE models and compared to another benchmark corpus.