Evaluation on the
<term>
ACE corpus
</term>
shows that effective incorporation of diverse
<term>
features
</term>
enables our system outperform previously best-reported systems on the 24
<term>
ACE relation subtypes
</term>
and significantly outperforms
<term>
tree kernel-based systems
</term>
by over 20 in
<term>
F-measure
</term>
on the 5
<term>
ACE relation types
</term>
.
<term>
Sentence boundary detection
</term>
in
<term>
speech
</term>
is important for enriching
<term>
speech recognition output
</term>
, making it easier for humans to read and downstream modules to process .
#9422Evaluation on the ACE corpus shows that effective incorporation of diverse features enables our system outperform previously best-reported systems on the 24 ACE relation subtypes and significantly outperforms tree kernel-based systems by over 20 in F-measure on the 5 ACE relation types.Sentence boundary detection in speech is important for enriching speech recognition output, making it easier for humans to read and downstream modules to process.