Search Results for author: Lasha Abzianidze

Found 19 papers, 9 papers with code

A Logic-Based Framework for Natural Language Inference in Dutch

1 code implementation7 Oct 2021 Lasha Abzianidze, Konstantinos Kogkalidis

Pairs of semantic terms are then fed to an automated theorem prover for natural logic which reasons with them while using the lexical relations found in the Open Dutch WordNet.

Natural Language Inference

DRS at MRP 2020: Dressing up Discourse Representation Structures as Graphs

1 code implementation CONLL 2020 Lasha Abzianidze, Johan Bos, Stephan Oepen

Discourse Representation Theory (DRT) is a formal account for representing the meaning of natural language discourse.

The Parallel Meaning Bank: A Framework for Semantically Annotating Multiple Languages

no code implementations29 Dec 2020 Lasha Abzianidze, Rik van Noord, Chunliu Wang, Johan Bos

This paper gives a general description of the ideas behind the Parallel Meaning Bank, a framework with the aim to provide an easy way to annotate compositional semantics for texts written in languages other than English.

Word Sense Disambiguation

MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing

no code implementations CONLL 2020 Stephan Oepen, Omri Abend, Lasha Abzianidze, Johan Bos, Jan Hajic, Daniel Hershcovich, Bin Li, Tim O{'}Gorman, Nianwen Xue, Daniel Zeman

Extending a similar setup from the previous year, five distinct approaches to the representation of sentence meaning in the form of directed graphs were represented in the English training and evaluation data for the task, packaged in a uniform graph abstraction and serialization; for four of these representation frameworks, additional training and evaluation data was provided for one additional language per framework.

Thirty Musts for Meaning Banking

no code implementations WS 2019 Johan Bos, Lasha Abzianidze

Meaning banking--creating a semantically annotated corpus for the purpose of semantic parsing or generation--is a challenging task.

Semantic Parsing

The First Shared Task on Discourse Representation Structure Parsing

no code implementations WS 2019 Lasha Abzianidze, Rik van Noord, Hessel Haagsma, Johan Bos

To measure similarity between two DRSs, they are represented in a clausal form, i. e. as a set of tuples.

DRS Parsing

CCGweb: a New Annotation Tool and a First Quadrilingual CCG Treebank

no code implementations WS 2019 Kilian Evang, Lasha Abzianidze, Johan Bos

We present the first open-source graphical annotation tool for combinatory categorial grammar (CCG), and the first set of detailed guidelines for syntactic annotation with CCG, for four languages: English, German, Italian, and Dutch.

Can neural networks understand monotonicity reasoning?

1 code implementation WS 2019 Hitomi Yanaka, Koji Mineshima, Daisuke Bekki, Kentaro Inui, Satoshi Sekine, Lasha Abzianidze, Johan Bos

Monotonicity reasoning is one of the important reasoning skills for any intelligent natural language inference (NLI) model in that it requires the ability to capture the interaction between lexical and syntactic structures.

Data Augmentation Natural Language Inference

Exploring Neural Methods for Parsing Discourse Representation Structures

1 code implementation TACL 2018 Rik van Noord, Lasha Abzianidze, Antonio Toral, Johan Bos

Neural methods have had several recent successes in semantic parsing, though they have yet to face the challenge of producing meaning representations based on formal semantics.

DRS Parsing

Evaluating Scoped Meaning Representations

2 code implementations LREC 2018 Rik van Noord, Lasha Abzianidze, Hessel Haagsma, Johan Bos

A pilot study is performed to automatically find changes in meaning by comparing meaning representations of translations.

Natural Language Understanding Semantic Parsing

Towards Universal Semantic Tagging

no code implementations WS 2017 Lasha Abzianidze, Johan Bos

The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags.

Semantic Parsing

LangPro: Natural Language Theorem Prover

1 code implementation EMNLP 2017 Lasha Abzianidze

LangPro is an automated theorem prover for natural language (https://github. com/kovvalsky/LangPro).

Automated Theorem Proving Natural Language Inference

The Parallel Meaning Bank: Towards a Multilingual Corpus of Translations Annotated with Compositional Meaning Representations

1 code implementation EACL 2017 Lasha Abzianidze, Johannes Bjerva, Kilian Evang, Hessel Haagsma, Rik van Noord, Pierre Ludmann, Duc-Duy Nguyen, Johan Bos

The Parallel Meaning Bank is a corpus of translations annotated with shared, formal meaning representations comprising over 11 million words divided over four languages (English, German, Italian, and Dutch).

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