BME-TUW at SR’20: Lexical grammar induction for surface realization

no code implementations • MSR (COLING) 2020 • Gábor Recski, Ádám Kovács, Kinga Gémes, Judit Ács, Andras Kornai

We present a system for mapping Universal Dependency structures to raw text which learns to restore word order by training an Interpreted Regular Tree Grammar (IRTG) that establishes a mapping between string and graph operations.

Sentence

TUW-Inf at GermEval2021: Rule-based and Hybrid Methods for Detecting Toxic, Engaging, and Fact-Claiming Comments

no code implementations • GermEval 2021 • Kinga Gémes, Gábor Recski

This paper describes our methods submitted for the GermEval 2021 shared task on identifying toxic, engaging and fact-claiming comments in social media texts (Risch et al., 2021).

POTATO: exPlainable infOrmation exTrAcTion framewOrk

1 code implementation • 31 Jan 2022 • Ádám Kovács, Kinga Gémes, Eszter Iklódi, Gábor Recski

We present POTATO, a task- and languageindependent framework for human-in-the-loop (HITL) learning of rule-based text classifiers using graph-based features.

Interpretable Machine Learning