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

Sastavljanje Hrvatske ovisnosne banke stabala: početne etape

The paper presents work–in–progress on the building of the Croatian Dependency Treebank. Its design principles, procedures and the pilot corpus used within are described. Perspectives for further development of the Croatian Dependency Treebank are presented at the end.Članak donosi međurezultate sastavljanja Hrvatske ovisnosne banke stabala koje je istraživanje u tijeku. Opisuju se njezina načela oblikovanja, postupci i uporabljeni pilot korpus. Na kraju se članka predstavljaju perspektive za daljnji razvitak Hrvatske ovisnosne banke stabala

Proceedings

Proceedings of the Ninth International Workshop on Treebanks and Linguistic Theories. Editors: Markus Dickinson, Kaili Müürisep and Marco Passarotti. NEALT Proceedings Series, Vol. 9 (2010), 268 pages. © 2010 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/15891

Projective dependency parsing with perceptron

We describe an online learning dependency parser for the CoNLL-X Shared Task, based on the bottom-up projective algorithm of Eisner (2000). We experiment with a large feature set that models: the tokens involved in dependencies and their immediate context, the surfacetext distance between tokens, and the syntactic context dominated by each dependency. In experiments, the treatment of multilingual information was totally blind.Peer ReviewedPostprint (author’s final draft

Investigating multilingual dependency parsing

In this paper, we describe a system for the CoNLL-X shared task of multilingual dependency parsing. It uses a baseline Nivre’s parser (Nivre, 2003) that first identifies the parse actions and then labels the dependency arcs. These two steps are implemented as SVM classifiers using LIBSVM. Features take into account the static context as well as relations dynamically built during parsing. We experimented two main additions to our implementation of Nivre’s parser: N-best search and bidirectional parsing. We trained the parser in both left-right and right-left directions and we combined the results. To construct a single-head, rooted, and cycle-free tree, we applied the Chu-Liu/Edmonds optimization algorithm. We ran the same algorithm with the same parameters on all the languages

Sastavljanje Hrvatske ovisnosne banke stabala: početne etape

The paper presents work–in–progress on the building of the Croatian Dependency Treebank. Its design principles, procedures and the pilot corpus used within are described. Perspectives for further development of the Croatian Dependency Treebank are presented at the end.Članak donosi međurezultate sastavljanja Hrvatske ovisnosne banke stabala koje je istraživanje u tijeku. Opisuju se njezina načela oblikovanja, postupci i uporabljeni pilot korpus. Na kraju se članka predstavljaju perspektive za daljnji razvitak Hrvatske ovisnosne banke stabala

A Robust Transformation-Based Learning Approach Using Ripple Down Rules for Part-of-Speech Tagging

In this paper, we propose a new approach to construct a system of transformation rules for the Part-of-Speech (POS) tagging task. Our approach is based on an incremental knowledge acquisition method where rules are stored in an exception structure and new rules are only added to correct the errors of existing rules; thus allowing systematic control of the interaction between the rules. Experimental results on 13 languages show that our approach is fast in terms of training time and tagging speed. Furthermore, our approach obtains very competitive accuracy in comparison to state-of-the-art POS and morphological taggers.Comment: Version 1: 13 pages. Version 2: Submitted to AI Communications - the European Journal on Artificial Intelligence. Version 3: Resubmitted after major revisions. Version 4: Resubmitted after minor revisions. Version 5: to appear in AI Communications (accepted for publication on 3/12/2015

Increasing Quality of the Corpus of Frequency Dictionary of Contemporary Polish for Morphosyntactic Tagging of the Polish Language

The paper is devoted to the issue of correction of the erroneous and ambiguous corpus of Frequency Dictionary of Contemporary Polish (FDCP) and its application to morphosyntactic tagging of the Polish language. Several stages of corpus transformation are presented and baseline part-of-speech tagging algorithms are evaluated, too

Abstract syntax as interlingua: Scaling up the grammatical framework from controlled languages to robust pipelines

Syntax is an interlingual representation used in compilers. Grammatical Framework (GF) applies the abstract syntax idea to natural languages. The development of GF started in 1998, first as a tool for controlled language implementations, where it has gained an established position in both academic and commercial projects. GF provides grammar resources for over 40 languages, enabling accurate generation and translation, as well as grammar engineering tools and components for mobile and Web applications. On the research side, the focus in the last ten years has been on scaling up GF to wide-coverage language processing. The concept of abstract syntax offers a unified view on many other approaches: Universal Dependencies, WordNets, FrameNets, Construction Grammars, and Abstract Meaning Representations. This makes it possible for GF to utilize data from the other approaches and to build robust pipelines. In return, GF can contribute to data-driven approaches by methods to transfer resources from one language to others, to augment data by rule-based generation, to check the consistency of hand-annotated corpora, and to pipe analyses into high-precision semantic back ends. This article gives an overview of the use of abstract syntax as interlingua through both established and emerging NLP applications involving GF

Treebank-based acquisition of Chinese LFG resources for parsing and generation

This thesis describes a treebank-based approach to automatically acquire robust,wide-coverage Lexical-Functional Grammar (LFG) resources for Chinese parsing and generation, which is part of a larger project on the rapid construction of deep, large-scale, constraint-based, multilingual grammatical resources. I present an application-oriented LFG analysis for Chinese core linguistic phenomena and (in cooperation with PARC) develop a gold-standard dependency-bank of Chinese f-structures for evaluation. Based on the Penn Chinese Treebank, I design and implement two architectures for inducing Chinese LFG resources, one annotation-based and the other dependency conversion-based. I then apply the f-structure acquisition algorithm together with external, state-of-the-art parsers to parsing new text into "proto" f-structures. In order to convert "proto" f-structures into "proper" f-structures or deep dependencies, I present a novel Non-Local Dependency (NLD) recovery algorithm using subcategorisation frames and f-structure paths linking antecedents and traces in NLDs extracted from the automatically-built LFG f-structure treebank. Based on the grammars extracted from the f-structure annotated treebank, I develop a PCFG-based chart generator and a new n-gram based pure dependency generator to realise Chinese sentences from LFG f-structures. The work reported in this thesis is the first effort to scale treebank-based, probabilistic Chinese LFG resources from proof-of-concept research to unrestricted, real text. Although this thesis concentrates on Chinese and LFG, many of the methodologies, e.g. the acquisition of predicate-argument structures, NLD resolution and the PCFG- and dependency n-gram-based generation models, are largely language and formalism independent and should generalise to diverse languages as well as to labelled bilexical dependency representations other than LFG