A generation-oriented workbench for performance grammar: Capturing linear order variability in German and Dutch

We describe a generation-oriented workbench for the Performance Grammar (PG) formalism, highlighting the treatment of certain word order and movement constraints in Dutch and German. PG enables a simple and uniform treatment of a heterogeneous collection of linear order phenomena in the domain of verb constructions (variably known as Cross-serial Dependencies, Verb Raising, Clause Union, Extraposition, Third Construction, Particle Hopping, etc.). The central data structures enabling this feature are clausal “topologies”: one-dimensional arrays associated with clauses, whose cells (“slots”) provide landing sites for the constituents of the clause. Movement operations are enabled by unification of lateral slots of topologies at adjacent levels of the clause hierarchy. The PGW generator assists the grammar developer in testing whether the implemented syntactic knowledge allows all and only the well-formed permutations of constituents

A generation-oriented workbench for performance grammar: Capturing linear order variability in German and Dutch

We describe a generation-oriented workbench for the Performance Grammar (PG) formalism, highlighting the treatment of certain word order and movement constraints in Dutch and German. PG enables a simple and uniform treatment of a heterogeneous collection of linear order phenomena in the domain of verb constructions (variably known as Cross-serial Dependencies, Verb Raising, Clause Union, Extraposition, Third Construction, Particle Hopping, etc.). The central data structures enabling this feature are clausal “topologies”: one-dimensional arrays associated with clauses, whose cells (“slots”) provide landing sites for the constituents of the clause. Movement operations are enabled by unification of lateral slots of topologies at adjacent levels of the clause hierarchy. The PGW generator assists the grammar developer in testing whether the implemented syntactic knowledge allows all and only the well-formed permutations of constituents

Using of Minimal Recursion Semantic representation for linguistic information

In this article will discuss current approaches to the representation of linguistic information. Particular attention is paid Minimal Recursion Semantic (MRS) and the Robust Minimal Recursion Semantic (RMRS) as one of the most promising directions. Shows the use of Minimal Recursion Semantic (MRS) for the Russian languag

Using of Minimal Recursion Semantic representation for linguistic information

In this article will discuss current approaches to the representation of linguistic information. Particular attention is paid Minimal Recursion Semantic (MRS) and the Robust Minimal Recursion Semantic (RMRS) as one of the most promising directions. Shows the use of Minimal Recursion Semantic (MRS) for the Russian language. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3177

Real bad grammar: realistic grammatical description with grammaticality

Sampson (this issue) argues for a concept of “realistic grammatical description” in which the distinction between grammatical and ungrammatical sentences is irrelevant. In this article I also argue for a concept of “realistic grammatical description” but one in which a binary distinction between grammatical and ungrammatical sentences is maintained. In distinguishing between the grammatical and ungrammatical, this kind of grammar differs from that proposed by Sampson, but it does share the important property that invented sentences have no role to play, either as positive or negative evidence

Corrective Feedback in Dialogue-based Computer Assisted Language Learning

Computer assisted language learning (CALL) systems are used by people to learn a language. CALL systems have provided a number of advantages for language learning such as their ability to provide consistent and flexible corrective feedback during the learning process. This feedback is expressed as information about what is ungrammatical or unacceptable in a target language. This paper presents a literature study on the field of corrective feedback and CALL and describes the future plan for my PhD research

Building a foundation of HPSG-based treebank on Bangla language

Includes bibliographical references (page 6).Now a day, the importance of a large annotated corpus for NLP researchers is widely known. In this paper, we describe an initial phase of developing a linguistically annotated corpus for non-configurational ‘Bangla’ language. Since, the formalism differs from those posited for configurational languages; several features have been added for constraint based parsing through HPSG-based formalism. We propose an outline of a semi-automated process by applying both case marking approach and some morphological analysis to constraint the parsing of a relatively free word order language for creating a linguistically rich, highly-lexicalized annotated corpus

A comparative evaluation of deep and shallow approaches to the automatic detection of common grammatical errors

This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses the XLE LFG parser and English grammar: two versions are presented, one which uses the XLE directly to perform the classification, and another one which uses a decision tree trained on features consisting of the XLE’s output statistics. The shallow processing approach predicts grammaticality based on n-gram frequency statistics: we present two versions, one which uses frequency thresholds and one which uses a decision tree trained on the frequencies of the rarest n-grams in the input sentence. We find that the use of a decision tree improves on the basic approach only for the deep parser-based approach. We also show that combining both the shallow and deep decision tree features is effective. Our evaluation is carried out using a large test set of grammatical and ungrammatical sentences. The ungrammatical test set is generated automatically by inserting grammatical errors into well-formed BNC sentences

A compositional and constraint-based approach to non-sentential utterances

Schlangen D, Lascarides A. A compositional and constraint-based approach to non-sentential utterances. In: Müller S, ed. Proceedings of the 10th international conference on Head-Driven Phrase Structure Grammar. East Lansing, Michigan, USA: CSLI Publications, Stanford, USA; 2003: 123-124