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The systematic errors listed above are the In our experiment we considered meaningful groups 2, 3, 4 only. Read the Text Version. Tommaso Caselli. The idea which stands behind our work was in- spired by the Optimality Theory OT applied to syntactic analysis , whose linguistic model makes the language itself coming from the interaction between conflicting constraints, and mainly consists of viewing the parsing process as a finite configurations problem that can be formulated as a constraint satisfaction problem CSP .
The Italian grammar has been expressed for the first time as a set of constraints that need to be satisfied by any parse tree.
The constraints propagation technique is then applied to re- strict possible analyses. Multiple solutions of a given sentence have been reduced to one structural disambiguation by weighting each relation of each different solution according to the number of occurrences of that re- lation in the indexed version of Italian Wikipedia created for the purpose.
A detailed analysis of the results is given, including some consideration on the difference between the LAS and UAS values. The attachment score obtained is The parser was tested against the Evalita DPT  dataset made available by the organizers after the competition and the results encouraged us to participate to Evalita The idea which stands behind our work was in- spired by the Optimality Theory OT applied to syntactic analysis , whose linguistic model makes the language itself coming from the interaction between conflicting constraints, and mainly consists of viewing the parsing process as a finite configurations problem that can be formulated as a constraint satisfaction problem CSP .
Deciding for this approach has been for us the logical con- sequence of the considerations we made after several research and experiments with top-down and mainly statistical graph-based [7, 13] and transition-based [22, 15, 1] bottom-up parsers.
We also analyzed in depth TULE , a particular rule-based parser which played a great role in our experiment developed by Leonardo Lesmo that got the best result LAS In our approach the dependency parsing problem is reduced to the problem of finding a dependency graph for a sentence that satisfies all the constraints defined by the grammar.
The structure of the system is made of two components: The first one has been implemented in Ada  us- ing Gecode  constraint programming  library which provides a constraint solver with state-of-the-art performances. A great effort has been required to de- fine the grammar that, as already stated, consists of a set of constraints needed to be satisfied by any parse tree.
We have first defined the general conditions for well-formed labeled tree, i. Subsequently we have encoded the Italian grammar subset of in a formalism inspired by the Slot Grammar SG  wherein every lexical entry contains informations about category, morphological features and a set of slots grammatical relations and rules dependency context constraints and word order constraints for filling them. Our wide coverage lexicon has been used, which includes subcategorization for nouns, adjectives, verbs and adverbs.
The grammar has been then fine-tuned on the TUT Treebank . While the constraint solver implements the constraint propagation to restrict possible solutions, the disambiguation module enters the game when the first module has brought to multiple solutions.
Please note that at this stage all the solutions satisfy all the constraints defined by the grammar. These multiple solutions represent a true structural ambiguity. One example is the well known prepositional phrase PP attachment e.
The module explores the tree of each solution and assigns a score to every arc connecting either the two conjuncts in a coordination or the two atoms of a PP.
The score of each of these relations in a given solution is computed by counting the number of occurrences of that relation in the Italian version of Wikipedia  previously analyzed by TULE parser and indexed by our Natural Language Indexer NLI. Since only one interpretation is allowed by Evalita DPT rules, in case of multiple solutions the one with the best score is chosen. Because of the specific role of the two components described above, the sys- tem can be considered a hybrid rule-based and statistical-based parser.
Our indexed version of the Italian Wikipedia can be explored at http: We also decided to evaluate the relationship between pars- ing accuracy and length of the sentences. To accomplish the above, we divided the set of sentences into five subsets groups of sentences whose lengths no. We than computed the average CSA for each group. The results are shown in Fig. In our experiment we considered meaningful groups 2, 3, 4 only. Table 1.
Please note that syntactic relations labels for which both recall and precision values are 0 have not been reported in the graph. Recall and Precision of every syntactic relation label attachment. Possible cause is that our lexicon has got a richer argumental structure than the one of the Gold dataset with respect to the given relation. Possible cause is that the Gold dataset has got a richer argumental structure than the one of our lexicon with respect to the given relation. Possible cause is the same of point no.
Reason for this is that the parser handles the non-projective linguistic phenomena in native mode. We did not implement the conversion to the projective con- figuration. The systematic errors listed above are the It is interesting to note that once the eight cases of error have been solved or accepted, the LAS value would be There is also an expected error related to the attachment to the modal verb.
In those sentences where a given atom e. Since our grammar follows the one of the TUT, this fact caused 14 errors the discrepancy in the annotation causes actually two errors for every occurrence. We trust the annotation of the TUT so we do not consider those be real errors.
Other discrepancies have been found between the Gold dataset and the TUT treebank that in agreement with Bosco and Lavelli  they have not been taken into account.
Attardi, G.: Experiments with a multilanguage non-projective dependency parser. Barbosa, P. Is the Best Good Enough? Optimality and Competition in Syntax.
Bosco, C. Annotation schema oriented evaluation for dependency pars- ing validation. Tartu 4. Evalita09 parsing task: Proceed- ings of Evalita09, Reggio Emilia , http: It is importantthat we feel free to spend our free time however we want, and feel no shame in kickingback and watching a movie or levelling up on our favorite game. Discovery isrewarding, allowing us to hit new highs and fall in love with things we never thought wewould.
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