Benchmark Dataset for Propaganda Detection in Czech Newspaper Texts

no code implementations • RANLP 2019 • V{\'\i}t Baisa, Ond{\v{r}}ej Herman, Ales Horak

Propaganda of various pressure groups ranging from big economies to ideological blocks is often presented in a form of objective newspaper texts.

Propaganda detection

DSL Shared Task 2016: Perfect Is The Enemy of Good Language Discrimination Through Expectation--Maximization and Chunk-based Language Model

no code implementations • WS 2016 • Ond{\v{r}}ej Herman, V{\'\i}t Suchomel, V{\'\i}t Baisa, Pavel Rychl{\'y}

In this paper we investigate two approaches to discrimination of similar languages: Expectation{--}maximization algorithm for estimating conditional probability P(word|language) and byte level language models similar to compression-based language modelling methods.

Language Modelling

Graded and Word-Sense-Disambiguation Decisions in Corpus Pattern Analysis: a Pilot Study

no code implementations • LREC 2016 • Silvie Cinkov{\'a}, Ema Krej{\v{c}}ov{\'a}, Anna Vernerov{\'a}, V{\'\i}t Baisa

The resource contains 11, 400 graded human decisions on usage patterns of 29 English lexical verbs, randomly selected from the Pattern Dictionary of English Verbs (Hanks, 2000 2014) based on their frequency and the number of senses their lemmas have in PDEV.

Word Sense Disambiguation

VPS-GradeUp: Graded Decisions on Usage Patterns

no code implementations • LREC 2016 • V{\'\i}t Baisa, Silvie Cinkov{\'a}, Ema Krej{\v{c}}ov{\'a}, Anna Vernerov{\'a}

We present VPS-GradeUp ― a set of 11, 400 graded human decisions on usage patterns of 29 English lexical verbs from the Pattern Dictionary of English Verbs by Patrick Hanks.

Clustering LEMMA

European Union Language Resources in Sketch Engine

no code implementations • LREC 2016 • V{\'\i}t Baisa, Jan Michelfeit, Marek Medve{\v{d}}, Milo{\v{s}} Jakub{\'\i}{\v{c}}ek

Several parallel corpora built from European Union language resources are presented here.

Increasing Coverage of Translation Memories with Linguistically Motivated Segment Combination Methods

no code implementations • WS 2015 • V{\'\i}t Baisa, Ale{\v{s}} Hor{\'a}k, Marek Medve{\v{d}}

Machine Translation Translation

SemEval-2015 Task 15: A CPA dictionary-entry-building task

no code implementations • SEMEVAL 2015 • V{\'\i}t Baisa, Jane Bradbury, Silvie Cinkov{\'a}, Isma{\"\i}l El Maarouf, Adam Kilgarriff, Octavian Popescu

Extrinsic Corpus Evaluation with a Collocation Dictionary Task

no code implementations • LREC 2014 • Adam Kilgarriff, Pavel Rychl{\'y}, Milo{\v{s}} Jakub{\'\i}{\v{c}}ek, Vojt{\v{e}}ch Kov{\'a}{\v{r}}, V{\'\i}t Baisa, Lucia Kocincov{\'a}

The NLP researcher or application-builder often wonders {``}what corpus should I use, or should I build one of my own?

Disambiguating Verbs by Collocation: Corpus Lexicography meets Natural Language Processing

no code implementations • LREC 2014 • Ismail El Maarouf, Jane Bradbury, V{\'\i}t Baisa, Patrick Hanks

This paper reports the results of Natural Language Processing (NLP) experiments in semantic parsing, based on a new semantic resource, the Pattern Dictionary of English Verbs (PDEV) (Hanks, 2013).

Semantic Parsing Word Sense Disambiguation

Automatic classification of semantic patterns from the Pattern Dictionary of English Verbs

no code implementations • WS 2013 • Isma{\"\i}l El Maarouf, V{\'\i}t Baisa

General Classification Machine Translation +1