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.
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.
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.
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).
no code implementations • 2 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.
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.
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.
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.
Ranked #6 on DRS Parsing on PMB-2.2.0
no code implementations • SEMEVAL 2017 • Dieke Oele, Kilian Evang
For pun interpretation, we use a knowledge-based Word Sense Disambiguation (WSD) method based on sense embeddings.
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).
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.
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?