Balázs Indig


2020

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The xtsv Framework and the Twelve Virtues of Pipelines
Balázs Indig | Bálint Sass | Iván Mittelholcz
Proceedings of the 12th Language Resources and Evaluation Conference

We present xtsv, an abstract framework for building NLP pipelines. It covers several kinds of functionalities which can be implemented at an abstract level. We survey these features and argue that all are desired in a modern pipeline. The framework has a simple yet powerful internal communication format which is essentially tsv (tab separated values) with header plus some additional features. We put emphasis on the capabilities of the presented framework, for example its ability to allow new modules to be easily integrated or replaced, or the variety of its usage options. When a module is put into xtsv, all functionalities of the system are immediately available for that module, and the module can be be a part of an xtsv pipeline. The design also allows convenient investigation and manual correction of the data flow from one module to another. We demonstrate the power of our framework with a successful application: a concrete NLP pipeline for Hungarian called e-magyar text processing system (emtsv) which integrates Hungarian NLP tools in xtsv. All the advantages of the pipeline come from the inherent properties of the xtsv framework.

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The ELTE.DH Pilot Corpus – Creating a Handcrafted Gigaword Web Corpus with Metadata
Balázs Indig | Árpád Knap | Zsófia Sárközi-Lindner | Mária Timári | Gábor Palkó
Proceedings of the 12th Web as Corpus Workshop

In this article, we present the method we used to create a middle-sized corpus using targeted web crawling. Our corpus contains news portal articles along with their metadata, that can be useful for diverse audiences, ranging from digital humanists to NLP users. The method presented in this paper applies rule-based components that allow the curation of the text and the metadata content. The curated data can thereon serve as a reference for various tasks and measurements. We designed our workflow to encourage modification and customisation. Our concept can also be applied to other genres of portals by using the discovered patterns in the architecture of the portals. We found that for a systematic creation or extension of a similar corpus, our method provides superior accuracy and ease of use compared to The Wayback Machine, while requiring minimal manpower and computational resources. Reproducing the corpus is possible if changes are introduced to the text-extraction process. The standard TEI format and Schema.org encoded metadata is used for the output format, but we stress that placing the corpus in a digital repository system is recommended in order to be able to define semantic relations between the segments and to add rich annotation.

2019

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One format to rule them all – The emtsv pipeline for Hungarian
Balázs Indig | Bálint Sass | Eszter Simon | Iván Mittelholcz | Noémi Vadász | Márton Makrai
Proceedings of the 13th Linguistic Annotation Workshop

We present a more efficient version of the e-magyar NLP pipeline for Hungarian called emtsv. It integrates Hungarian NLP tools in a framework whose individual modules can be developed or replaced independently and allows new ones to be added. The design also allows convenient investigation and manual correction of the data flow from one module to another. The improvements we publish include effective communication between the modules and support of the use of individual modules both in the chain and standing alone. Our goals are accomplished using extended tsv (tab separated values) files, a simple, uniform, generic and self-documenting input/output format. Our vision is maintaining the system for a long time and making it easier for external developers to fit their own modules into the system, thus sharing existing competencies in the field of processing Hungarian, a mid-resourced language. The source code is available under LGPL 3.0 license at https://github.com/dlt-rilmta/emtsv .

2018

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What’s Wrong, Python? – A Visual Differ and Graph Library for NLP in Python
Balázs Indig | András Simonyi | Noémi Ligeti-Nagy
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

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E-magyar – A Digital Language Processing System
Tamás Váradi | Eszter Simon | Bálint Sass | Iván Mittelholcz | Attila Novák | Balázs Indig | Richárd Farkas | Veronika Vincze
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)

2016

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Mapping Ontologies Using Ontologies: Cross-lingual Semantic Role Information Transfer
Balázs Indig | Márton Miháltz | András Simonyi
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

This paper presents the process of enriching the verb frame database of a Hungarian natural language parser to enable the assignment of semantic roles. We accomplished this by linking the parser’s verb frame database to existing linguistic resources such as VerbNet and WordNet, and automatically transferring back semantic knowledge. We developed OWL ontologies that map the various constraint description formalisms of the linked resources and employed a logical reasoning device to facilitate the linking procedure. We present results and discuss the challenges and pitfalls that arose from this undertaking.