The jointparser is a parser that jointly annotates syntax and semantics.

It performs syntactic parsing, shallow semantic parsing and predicate identification.
And it is one of the few parsers that simultaneously learns and annotates syntax and semantics.

We extended the Eisner algorithm to annotate semantics by assigning semantic links at each dependency scoring step. The learning is based on an averaged Perceptron.

For efficiency reasons, some syntax-based features used in the semantic classifier are pre-computed. The predicate identification is done as a previous step. The implementation of our model does not give us an optimal syntactic-semantic tree as we pre-compute some features.

The system description can be found at:

Software used in this demo:

To try this parser just write a sentence:

click and please wait few seconds...