LangPro: Natural Language Theorem Prover

LangPro is an automated theorem prover for natural language (https://github.com/kovvalsky/LangPro). Given a set of premises and a hypothesis, it is able to prove semantic relations between them. The prover is based on a version of analytic tableau method specially designed for natural logic. The proof procedure operates on logical forms that preserve linguistic expressions to a large extent. %This property makes the logical forms easily obtainable from syntactic trees. %, in particular, Combinatory Categorial Grammar derivation trees. The nature of proofs is deductive and transparent. On the FraCaS and SICK textual entailment datasets, the prover achieves high results comparable to state-of-the-art.Comment: 6 pages, 8 figures, Conference on Empirical Methods in Natural Language Processing (EMNLP) 201

Towards Universal Semantic Tagging

The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags. We argue that the task, with its independent nature, contributes to better semantic analysis for wide-coverage multilingual text. We present the initial version of the semantic tagset and show that (a) the tags provide semantically fine-grained information, and (b) they are suitable for cross-lingual semantic parsing. An application of the semantic tagging in the Parallel Meaning Bank supports both of these points as the tags contribute to formal lexical semantics and their cross-lingual projection. As a part of the application, we annotate a small corpus with the semantic tags and present new baseline result for universal semantic tagging.Comment: 9 pages, International Conference on Computational Semantics (IWCS

Formal Proofs as Structured Explanations: Proposing Several Tasks on Explainable Natural Language Inference

In this position paper, we propose a way of exploiting formal proofs to put forward several explainable natural language inference (NLI) tasks. The formal proofs will be produced by a reliable and high-performing logic-based NLI system. Taking advantage of the in-depth information available in the generated formal proofs, we show how it can be used to define NLI tasks with structured explanations. The proposed tasks can be ordered according to difficulty defined in terms of the granularity of explanations. We argue that the tasks will suffer with substantially fewer shortcomings than the existing explainable NLI tasks (or datasets).Comment: 7 pages, 2 figure

Thirty Musts for Meaning Banking

Meaning banking--creating a semantically annotated corpus for the purpose of semantic parsing or generation--is a challenging task. It is quite simple to come up with a complex meaning representation, but it is hard to design a simple meaning representation that captures many nuances of meaning. This paper lists some lessons learned in nearly ten years of meaning annotation during the development of the Groningen Meaning Bank (Bos et al., 2017) and the Parallel Meaning Bank (Abzianidze et al., 2017). The paper's format is rather unconventional: there is no explicit related work, no methodology section, no results, and no discussion (and the current snippet is not an abstract but actually an introductory preface). Instead, its structure is inspired by work of Traum (2000) and Bender (2013). The list starts with a brief overview of the existing meaning banks (Section 1) and the rest of the items are roughly divided into three groups: corpus collection (Section 2 and 3, annotation methods (Section 4-11), and design of meaning representations (Section 12-30). We hope this overview will give inspiration and guidance in creating improved meaning banks in the future.Comment: https://www.aclweb.org/anthology/W19-3302

An HPSG-based Formal Grammar of a Core Fragment of Georgian Implemented in TRALE

Gruzínština se výrazně odlišuje od indoevropských jazyků. Vyznačuje se řadou jazykových jevů, které jsou obtížné pro lingvistickou teorii i počítačové zpracování. Navíc patří mezi jazyky, u kterých nelze plně využít existující zdroje, a není ani dostatečně prozkoumána z hlediska matematické lingvistiky. Cílem této práce je vytvořit formální gramatiku morfologie a syntaxe jádra gruzínštiny. Tato formální gramatika vychází z teorie HPSG, která je v současnosti jedním z nejúspěšnějších rámců pro formální popis jazyka. Gramatiku implementujeme v systému TRALE, který umožňuje věrné zachycení ručně psaných gramatik založených na HPSG. Tato práce je první aplikací teorie HPSG na gruzínštinu.Georgian is remarkably different from Indo-European languages. The language has several linguistic phenomena that are challenging both from theoretical and computational points of view. In addition, it is low- resourced and insufficiently studied from the computational point of view. In the thesis, we model morphology and syntax of a core fragment of the language in a formal grammar. Namely, the formal grammar is written in the HPSG framework - one of the most powerful grammar frameworks nowadays. We also implement the grammar in TRALE - a grammar implementation platform, which is faithful to "hand-written" HPSG-based grammars. Note that this is the first application of HPSG to Georgian.Institute of Formal and Applied LinguisticsÚstav formální a aplikované lingvistikyFaculty of Mathematics and PhysicsMatematicko-fyzikální fakult