Search Results for author: Kilian Evang

Found 20 papers, 4 papers with code

Configurable Dependency Tree Extraction from CCG Derivations

no code implementations UDW (COLING) 2020 Kilian Evang

We revisit the problem of extracting dependency structures from the derivation structures of Combinatory Categorial Grammar (CCG).

DRS Parsing as Sequence Labeling

no code implementations *SEM (NAACL) 2022 Minxing Shen, Kilian Evang

We present the first fully trainable semantic parser for English, German, Italian, and Dutch discourse representation structures (DRSs) that is competitive in accuracy with recent sequence-to-sequence models and at the same time {emph{compositional} in the sense that the output maps each token to one of a finite set of meaning {emph{fragments}, and the meaning of the utterance is a function of the meanings of its parts.

DRS Parsing

RRGparbank: A Parallel Role and Reference Grammar Treebank

1 code implementation LREC 2022 Tatiana Bladier, Kilian Evang, Valeria Generalova, Zahra Ghane, Laura Kallmeyer, Robin Möllemann, Natalia Moors, Rainer Osswald, Simon Petitjean

This paper describes the first release of RRGparbank, a multilingual parallel treebank for Role and Reference Grammar (RRG) containing annotations of George Orwell’s novel 1984 and its translations.

Improving Low-resource RRG Parsing with Cross-lingual Self-training

no code implementations COLING 2022 Kilian Evang, Laura Kallmeyer, Jakub Waszczuk, Kilu von Prince, Tatiana Bladier, Simon Petitjean

Starting from an existing RRG parser, we propose two strategies for low-resource parsing: first, we extend the parsing model into a cross-lingual parser, exploiting the parallel data in the high-resource language and unsupervised word alignments by providing internal states of the source-language parser to the target-language parser.

Constituency Parsing

Dissecting Paraphrases: The Impact of Prompt Syntax and supplementary Information on Knowledge Retrieval from Pretrained Language Models

no code implementations2 Apr 2024 Stephan Linzbach, Dimitar Dimitrov, Laura Kallmeyer, Kilian Evang, Hajira Jabeen, Stefan Dietze

Typically, designing these prompts is a tedious task because small differences in syntax or semantics can have a substantial impact on knowledge retrieval performance.


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.

Cross-lingual CCG Induction

1 code implementation NAACL 2019 Kilian Evang

Combinatory categorial grammars are linguistically motivated and useful for semantic parsing, but costly to acquire in a supervised way and difficult to acquire in an unsupervised way.

POS Semantic Parsing

Transition-based DRS Parsing Using Stack-LSTMs

no code implementations WS 2019 Kilian Evang

We present our submission to the IWCS 2019 shared task on semantic parsing, a transition-based parser that uses explicit word-meaning pairings, but no explicit representation of syntax.

DRS Parsing

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).

Cross-lingual Learning of an Open-domain Semantic Parser

no code implementations COLING 2016 Kilian Evang, Johan Bos

We propose a method for learning semantic CCG parsers by projecting annotations via a parallel corpus.

Semantic Parsing

Developing a large semantically annotated corpus

no code implementations LREC 2012 Valerio Basile, Johan Bos, Kilian Evang, Noortje Venhuizen

What would be a good method to provide a large collection of semantically annotated texts with formal, deep semantics rather than shallow?

Boundary Detection Part-Of-Speech Tagging

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