This paper presents a resource-centric study of link prediction approaches over French lexical-semantic graphs. Our study incorporates two graphs, RezoJDM16k and RL-fr, and we evaluated seven link prediction models, with CompGCN-ConvE emerging as the best performer. We also conducted a qualitative analysis of the predictions using manual annotations. Based on this, we found that predictions with higher confidence scores were more valid for inclusion. Our findings highlight different benefits for the dense graph compared to the sparser graph RL-fr. While the addition of new triples to RezoJDM16k offers limited advantages, RL-fr can benefit substantially from our approach.
In this paper, we compare different ways to annotate both syntactic and morphological relations in a dependency treebank and we propose new formats we call mSUD and mUD, compatible with the Universal Dependencies (UD) schema for syntactic treebanks. We emphasize mSUD rather than mUD, the former being based on distributional criteria for the choice of the head of any combination, which allow us to clearly encode the internal structure of a word, that is, the derivational path. We investigate different problems posed by a morph-based annotation, concerning tokenization, choice of the head of a morph combination, relations between morphs, additional features needed, such as the token type differentiating roots and derivational and inflectional affixes. We show how our annotation schema can be applied to different languages from polysynthetic languages such as Yupik to isolating languages such as Chinese.
This paper presents a new phonetic resource for Nigerian Pidgin, a low-resource language of West Africa. Aiming to provide a new tool for research on intonosyntax, we have augmented an existing syntactic treebank of Nigerian Pidgin, associating each orthographically transcribed token with a series of syllable-level alignments and phonetizations. Syllables are further described using a set of continuous and discrete prosodic features. This new approach provides a simple tool for researchers to explore the prosodic characteristics of various syntactic phenomena. In this paper, we present the format of the corpus, the various features added, and several explorations that can be performed using an online interface. We also present a prosodically specified lexicon extracted using this resource. In it, each orthographic form is accompanied by the frequency of its phoneme-level variants, as well as the suprasegmental features that most frequently accompany each syllable. Finally, we present several additional case studies on how this corpus can used in the study of the language’s prosody.
This paper presents the creation of Hostomytho, a game with a purpose intended for evaluating the quality of synthetic biomedical texts through multiple mini-games. Hostomytho was developed entirely using open source technologies both for internet browser and mobile platforms (IOS & Android). The code and the annotations created for synthetic clinical cases in French will be made freely available.
In this paper, we present the first version of YARN, a new semantic representation formalism. We propose this new formalism to unify the advantages of logic-based formalisms while retaining direct interpretation, making it widely usable. YARN is rooted in the encoding of different semantic phenomena as separate layers. We begin by presenting a formal definition of the mathematical structure that constitutes YARN. We then illustrate with concrete examples how this structure can be used in the context of semantic representation for encoding multiple phenomena (such as modality, negation and quantification) as layers built on top of a central predicate-argument structure. The benefit of YARN is that it allows for the independent annotation and analysis of different phenomena as they are easy to “switch off”. Furthermore, we have explored YARN’s ability to encode simple interactions between phenomena. We wrap up the work presented by a discussion of some of the interesting observations made during the development of YARN so far and outline our extensive future plans for this formalism.
This paper presents the objectives, organization and activities of the UniDive COST Action, a scientific network dedicated to universality, diversity and idiosyncrasy in language technology. We describe the objectives and organization of this initiative, the people involved, the working groups and the ongoing tasks and activities. This paper is also an pen call for participation towards new members and countries.
The area of designing semantic/meaning representations is a dynamic one with new formalisms and extensions being proposed continuously. It may be challenging for users of semantic representations to select the relevant formalism for their purpose or for newcomers to the field to select the features they want to represent in a new formalism. In this paper, we propose a set of structural and global features to consider when designing formalisms, and against which formalisms can be compared. We also propose a sample comparison of a number of existing formalisms across the selected features, complemented by a more entailment-oriented comparison on the phenomena of the FraCaS corpus.
We present version 1.3 of the PARSEME multilingual corpus annotated with verbal multiword expressions. Since the previous version, new languages have joined the undertaking of creating such a resource, some of the already existing corpora have been enriched with new annotated texts, while others have been enhanced in various ways. The PARSEME multilingual corpus represents 26 languages now. All monolingual corpora therein use Universal Dependencies v.2 tagset. They are (re-)split observing the PARSEME v.1.2 standard, which puts impact on unseen VMWEs. With the current iteration, the corpus release process has been detached from shared tasks; instead, a process for continuous improvement and systematic releases has been introduced.
We present a graph-based tool which can be used to explore Verbal Multi-Word Expression (VMWE) annotated in the Parseme project. The tool can be used for linguistic exploration on the data, for helping the manual annotation process and to search for errors or inconsistencies in the annotations.
A number of graph-based semantic representation frameworks have emerged in recent years, but there are few parallel annotated corpora across them. We want to explore the viability of transforming graphs from one framework into another to construct parallel datasets. In this work, we consider graph rewriting from Discourse Representation Structures (Parallel Meaning Bank (PMB) variant) to Abstract Meaning Representation (AMR). We first build a gold AMR corpus of 102 sentences from the PMB. We then construct a rule base, aided by a further 95 sentences. No benchmark for this task exists, so we compare our system’s output to that of state-of-the-art AMR parsers, and explore the more challenging cases. Finally, we discuss where the two frameworks diverge in encoding semantic phenomena.
Au début du XXIe siècle, le français faisait encore partie des langues peu dotées. Grâce aux efforts de la communauté française du traitement automatique des langues (TAL), de nombreuses ressources librement disponibles ont été produites, dont des lexiques du français. À travers cet article, nous nous intéressons à leur devenir dans la communauté par le prisme des actes de la conférence TALN sur une période de 20 ans.
Ce projet de recherche vise à créer de nouveaux treebanks en dépendance pour des langues sous-dotées, en unifiant autant que possible leur développement avec celui de grammaires descriptives quantitatives. Nous présenterons notre chaîne de traitement et de développement de treebanks et nous discuterons du type de grammaire que nous voulons extraire. Enfin, nous examinerons l’utilisation de ces ressources en typologie quantitative.
This paper describes the continuation of a project that aims at establishing an interoperable annotation schema for quantification phenomena as part of the ISO suite of standards for semantic annotation, known as the Semantic Annotation Framework. After a break, caused by the Covid-19 pandemic, the project was relaunched in early 2022 with a second working draft of an annotation scheme, which is discussed in this paper. Keywords: semantic annotation, quantification, interoperability, annotation schema, ISO standard
This paper presents how the online tool Grew-match can be used to make queries and visualise data from existing semantically annotated corpora. A dedicated syntax is available to construct simple to complex queries and execute them against a corpus. Such queries give transverse views of the annotated data, this views can help for checking the consistency of annotations in one corpus or across several corpora. Grew-match can then be seen as an error mining tool: when inconsistencies are detected, it helps finding the sentences which should be fixed. Finally, Grew-match can also be used as a side tool to assist annotation task helping to find annotations examples in existing corpora to be compare to the data to be annotated.
In this paper, we consider two of the currently popular semantic frameworks: Abstract Meaning Representation (AMR) - a more abstract framework, and Universal Conceptual Cognitive Annotation (UCCA) - an anchored framework. We use a corpus-based approach to build two graph rewriting systems, a deterministic and a non-deterministic one, from the former to the latter framework. We present their evaluation and a number of ambiguities that we discovered while building our rules. Finally, we provide a discussion and some future work directions in relation to comparing semantic frameworks of different flavors.
This article presents a set of tools built around the Graph Rewriting computational framework which can be used to compute complex rule-based transformations on linguistic structures. Application of the graph matching mechanism for corpus exploration, error mining or quantitative typology are also given.
This paper details experiments we performed on the Universal Dependencies 2.7 corpora in order to investigate the dominant word order in the available languages. For this purpose, we used a graph rewriting tool, GREW, which allowed us to go beyond the surface annotations and identify the implicit subjects. We first measured the distribution of the six different word orders (SVO, SOV, VSO, VOS, OVS, OSV) in the corpora and investigated when there was a significant difference in the corpora within a given language. Then, we compared the obtained results with information provided in the WALS database (Dryer and Haspelmath, 2013) and in ( ̈Ostling, 2015). Finally, we examined the impact of using a graph rewriting tool for this task. The tools and resources used for this research are all freely available.
This paper describes a system proposed for the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies (EUD). We propose a Graph Rewriting based system for computing Enhanced Universal Dependencies, given the Basic Universal Dependencies (UD).
We present here Rigor Mortis, a gamified crowdsourcing platform designed to evaluate the intuition of the speakers, then train them to annotate multi-word expressions (MWEs) in French corpora. We previously showed that the speakers’ intuition is reasonably good (65% in recall on non-fixed MWE). We detail here the annotation results, after a training phase using some of the tests developed in the PARSEME-FR project.
In this paper we present Arborator-Grew, a collaborative annotation tool for treebank development. Arborator-Grew combines the features of two preexisting tools: Arborator and Grew. Arborator is a widely used collaborative graphical online dependency treebank annotation tool. Grew is a tool for graph querying and rewriting specialized in structures needed in NLP, i.e. syntactic and semantic dependency trees and graphs. Grew also has an online version, Grew-match, where all Universal Dependencies treebanks in their classical, deep and surface-syntactic flavors can be queried. Arborator-Grew is a complete redevelopment and modernization of Arborator, replacing its own internal database storage by a new Grew API, which adds a powerful query tool to Arborator’s existing treebank creation and correction features. This includes complex access control for parallel expert and crowd-sourced annotation, tree comparison visualization, and various exercise modes for teaching and training of annotators. Arborator-Grew opens up new paths of collectively creating, updating, maintaining, and curating syntactic treebanks and semantic graph banks.
This paper presents a French version of the FraCaS test suite. This test suite, originally written in English, contains problems illustrating semantic inference in natural language. We describe linguistic choices we had to make when translating the FraCaS test suite in French, and discuss some of the issues that were raised by the translation. We also report an experiment we ran in order to test both the translation and the logical semantics underlying the problems of the test suite. This provides a way of checking formal semanticists’ hypotheses against actual semantic capacity of speakers (in the present case, French speakers), and allow us to compare the results we obtained with the ones of similar experiments that have been conducted for other languages.
We present edition 1.2 of the PARSEME shared task on identification of verbal multiword expressions (VMWEs). Lessons learned from previous editions indicate that VMWEs have low ambiguity, and that the major challenge lies in identifying test instances never seen in the training data. Therefore, this edition focuses on unseen VMWEs. We have split annotated corpora so that the test corpora contain around 300 unseen VMWEs, and we provide non-annotated raw corpora to be used by complementary discovery methods. We released annotated and raw corpora in 14 languages, and this semi-supervised challenge attracted 7 teams who submitted 9 system results. This paper describes the effort of corpus creation, the task design, and the results obtained by the participating systems, especially their performance on unseen expressions.
This article presents the results we obtained in crowdsourcing French speakers’ intuition concerning multi-work expressions (MWEs). We developed a slightly gamified crowdsourcing platform, part of which is designed to test users’ ability to identify MWEs with no prior training. The participants perform relatively well at the task, with a recall reaching 65% for MWEs that do not behave as function words.
This article proposes a surface-syntactic annotation scheme called SUD that is near-isomorphic to the Universal Dependencies (UD) annotation scheme while following distributional criteria for defining the dependency tree structure and the naming of the syntactic functions. Rule-based graph transformation grammars allow for a bi-directional transformation of UD into SUD. The back-and-forth transformation can serve as an error-mining tool to assure the intra-language and inter-language coherence of the UD treebanks.
Nous avons précédemment montré qu’il est possible de faire produire des annotations syntaxiques de qualité par des participants à un jeu ayant un but. Nous présentons ici les résultats d’une expérience visant à évaluer leur production sur un corpus plus complexe, en langue de spécialité, en l’occurrence un corpus de textes scientifiques sur l’ADN. Nous déterminons précisément la complexité de ce corpus, puis nous évaluons les annotations en syntaxe de dépendances produites par les joueurs par rapport à une référence mise au point par des experts du domaine.
This article presents the results we obtained on a complex annotation task (that of dependency syntax) using a specifically designed Game with a Purpose, ZombiLingo. We show that with suitable mechanisms (decomposition of the task, training of the players and regular control of the annotation quality during the game), it is possible to obtain annotations whose quality is significantly higher than that obtainable with a parser, provided that enough players participate. The source code of the game and the resulting annotated corpora (for French) are freely available.
We define a deep syntactic representation scheme for French, which abstracts away from surface syntactic variation and diathesis alternations, and describe the annotation of deep syntactic representations on top of the surface dependency trees of the Sequoia corpus. The resulting deep-annotated corpus, named deep-sequoia, is freely available, and hopefully useful for corpus linguistics studies and for training deep analyzers to prepare semantic analysis.
This article presents experiments aiming at mapping the Lexique des Verbes du Français (Lexicon of French Verbs) to FRILEX, a Natural Language Processing (NLP) lexicon based on D ICOVALENCE. The two resources (Lexicon of French Verbs and D ICOVALENCE) were built by linguists, based on very different theories, which makes a direct mapping nearly impossible. We chose to use the examples provided in one of the resource to find implicit links between the two and make them explicit.
Nous montrons comment enrichir une annotation en dépendances syntaxiques au format du French Treebank de Paris 7 en utilisant la réécriture de graphes, en vue du calcul de sa représentation sémantique. Le système de réécriture est composé de règles grammaticales et lexicales structurées en modules. Les règles lexicales utilisent une information de contrôle extraite du lexique des verbes français Dicovalence.
Cet article propose une méthode pour calculer les dépendances syntaxiques d’un énoncé à partir du processus d’analyse en constituants. L’objectif est d’obtenir des dépendances complètes c’est-à-dire contenant toutes les informations nécessaires à la construction de la sémantique. Pour l’analyse en constituants, on utilise le formalisme des grammaires d’interaction : celui-ci place au cœur de la composition syntaxique un mécanisme de saturation de polarités qui peut s’interpréter comme la réalisation d’une relation de dépendance. Formellement, on utilise la notion de motifs de graphes au sens de la réécriture de graphes pour décrire les conditions nécessaires à la création d’une dépendance.
Nous définissons le beta-calcul, un calcul de réécriture de graphes, que nous proposons d’utiliser pour étudier les liens entre différentes représentations linguistiques. Nous montrons comment transformer une analyse syntaxique en une représentation sémantique par la composition de deux jeux de règles de beta-calcul. Le premier souligne l’importance de certaines informations syntaxiques pour le calcul de la sémantique et explicite le lien entre syntaxe et sémantique sous-spécifiée. Le second décompose la recherche de modèles pour les représentations sémantiques sous-spécifiées.
Nous présentons ici l’analyseur syntaxique LEOPAR basé sur les grammaires d’interaction ainsi que d’autres outils utiles pour notre chaîne de traitement syntaxique.
Cet article propose une méthode pour extraire une analyse en dépendances d’un énoncé à partir de son analyse en constituants avec les grammaires d’interaction. Les grammaires d’interaction sont un formalisme grammatical qui exprime l’interaction entre les mots à l’aide d’un système de polarités. Le mécanisme de composition syntaxique est régi par la saturation des polarités. Les interactions s’effectuent entre les constituants, mais les grammaires étant lexicalisées, ces interactions peuvent se traduire sur les mots. La saturation des polarités lors de l’analyse syntaxique d’un énoncé permet d’extraire des relations de dépendances entre les mots, chaque dépendance étant réalisée par une saturation. Les structures de dépendances ainsi obtenues peuvent être vues comme un raffinement de l’analyse habituellement effectuée sous forme d’arbre de dépendance. Plus généralement, ce travail apporte un éclairage nouveau sur les liens entre analyse en constituants et analyse en dépendances.
La production de lexiques est une activité indispensable mais complexe, qui nécessite, quelle que soit la méthode de création utilisée (acquisition automatique ou manuelle), une validation humaine. Nous proposons dans ce but une plate-forme Web librement disponible, appelée Sylva (Systematic lexicon validator). Cette plate-forme a pour caractéristiques principales de permettre une validation multi-niveaux (par des validateurs, puis un expert) et une traçabilité de la ressource. La tâche de l’expert(e) linguiste en est allégée puisqu’il ne lui reste à considérer que les données sur lesquelles il n’y a pas d’accord inter-validateurs.
PrepLex est un lexique des prépositions du français. Il contient les informations utiles à des systèmes d’analyse syntaxique. Il a été construit en comparant puis fusionnant différentes sources d’informations lexicales disponibles. Ce lexique met également en évidence les prépositions ou classes de prépositions qui apparaissent dans la définition des cadres de sous-catégorisation des ressources lexicales qui décrivent la valence des verbes.
Les tables du LADL (Laboratoire d’Automatique Documentaire et Linguistique) contiennent des données électroniques extensives sur les propriétés morphosyntaxiques et syntaxiques des foncteurs syntaxiques du français (verbes, noms, adjectifs). Ces données, dont on sait qu’elles sont nécessaires pour le bon fonctionnement des systèmes de traitement automatique des langues, ne sont cependant que peu utilisées par les systèmes actuels. Dans cet article, nous identifions les raisons de cette lacune et nous proposons une méthode de conversion des tables vers un format mieux approprié au traitement automatique des langues.