This work analyses the benefits of applying metrics based on the occurrence of words and
their neighbourhoods in documents to a set of relational triples automatically extracted from
corpora. In our experimentation, we start by using a simple system to extract semantic triples
from a corpus. Then, the same corpus is used for weighting each triple according to well-
known distributional metrics. Finally, we take some conclusions on the correlation between
the values given by the metrics and the evaluation made by humans.