A Treebank-based Investigation of IPP-triggering Verbs in Dutch

In this paper, we discuss the constraints and measures evaluated by [8], [12].
We evaluate these measures on IL treebanks, following with the adequate linguistic
description of non-projective structures, focusing on the identification and categorization
of grammatical structures that can readily undergo non-projectivity and the
possible reasons for the same.
The paper is organized as follows: In Section 2, we give an overview of Indian
Language Treebanking with reference to the treebanks used in this work. Section
3 discusses different constraints on dependency trees followed by the empirical
results of our experiments in Section 4. In Section 5, we present an in depth analysis
of non-projective structures approved by Indian Languages. Finally Section 6
concludes the paper.
2 Treebanks
In our analysis of non-projective structures in Indian languages, we use treebanks
of four languages namely Hindi, Urdu, Bangla and Telugu. These treebanks are
currently being developed following the annotation scheme based on the Computational
Paninian Grammar (CPG) [1]. The dependency relations in these treebanks,
under this framework, are marked between chunks. A chunk is a minimal,
non-recursive structure consisting of a group of closely related words. Thus, in
these treebanks a node in a dependency tree is represented by a chunk and not by a
word. Table 1 gives an overview of the four above mentioned treebanks. While the
Hindi treebanking effort has matured and grown considerably [2] the other three
treebanks are still at an initial stage of development. Because of the large size and
stable annotations, Hindi treebank provides major insights into potential sites of
non-projectivity. In our work we have ignored intra-chunk dependencies for two
reasons 1) currently intra-chunk dependencies are not being marked in the treebanks,
and 2) intra-chunk dependencies are projective; all the non-projective edges are
distributed among the inter-chunk relations (as is the case with Hindi [10]).
Language Sentences Words / Sentences Chunks /Sentences
Hindi 20705 20.8 10.7
Urdu 3226 29.1 13.7
Bangla 1279 9.5 6.4
Telugu 1635 9.4 3.9
Table 1: IL TREEBANK STATISTICS
In comparison to other free word order languages like Czech and Danish which
have non-projectivity in 23% (out of 73088 sentences) and 15% (out of 4393 sentences)
respectively [8], [5], Indian languages show interesting figures, Urdu has
highest number of non-projective sentences, out of 3226 sentences 23% are nonprojective,
in Hindi the number drops to 15% out of 20705 sentences, in Bangla
5% of 1279 sentences and interestingly there are no non-projective dependency
structures in Telugu treebank.
3 Dependency Graph and its properties
In this section, we give a formal definition of dependency tree, and subsequently
define different constraints on these dependency trees like projectivity, planarity
and well-nestedness.
Dependency Tree : A dependency tree D = (V, E, ≼) is a directed graph with V a set
of nodes, E a set of edges showing a dependency relation on V, and ≼ linear order on V.
Every dependency tree satisfies two properties : a) it is acyclic, and b) all nodes
have in-degree 1, except root node with in-degree 0.
3.1 Condition of Projectivity
Condition of projectivity in contrast to acyclicity and in-degree concerns the interaction
between the dependency relations and the projection of a these relations on
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