Abstract
We present a comparison between two systems
for establishing syntactic and semantic dependencies: one that performs dependency parsing
and semantic role labeling as a single task, and
another that performs the two tasks in isolation. The systems are based on local memorybased classifiers predicting syntactic and semantic dependency relations between pairs of words.
In a second global phase, the systems perform
a deterministic ranking procedure in which the
output of the local classifiers is combined per
sentence into a dependency graph and semantic role labeling assignments for all predicates.
The comparison shows that in the learning phase
a joint approach produces better-scoring classifiers, while after the ranking phase the isolated
approach produces the most accurate syntactic
dependencies, while the joint approach yields the
most accurate semantic role assignments.
for establishing syntactic and semantic dependencies: one that performs dependency parsing
and semantic role labeling as a single task, and
another that performs the two tasks in isolation. The systems are based on local memorybased classifiers predicting syntactic and semantic dependency relations between pairs of words.
In a second global phase, the systems perform
a deterministic ranking procedure in which the
output of the local classifiers is combined per
sentence into a dependency graph and semantic role labeling assignments for all predicates.
The comparison shows that in the learning phase
a joint approach produces better-scoring classifiers, while after the ranking phase the isolated
approach produces the most accurate syntactic
dependencies, while the joint approach yields the
most accurate semantic role assignments.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 7th International Conference on Recent Advances in Natural Language Processing (RANLP-2009) |
| Publisher | Association for Computational Linguistics |
| Publication status | Published - 2009 |