Exploitation d'un corpus annoté pour l'analyse des relations causales

This study aims at offering, from the observation of attested data, a description of causalrelations in the framework of a representational theory of discourse called SDRT. Exploring acorpus of texts, which are annotated at discourse-level, allowed us to confront the theory withreal data. Upon realising that SDRT did not reflect the diversity of causal relations that couldbe observed in texts, we offer to enrich the theoretical model on the basis of our observations.For further analysis, we are planning on expanding our corpus in order to make it morerepresentative.Notre étude vise à proposer, à partir de lobservation dénoncés attestés, une description desrelations causales dans le cadre dune théorie représentationnelle du discours, la SDRT.Lexploitation dun corpus de textes enrichis dannotations discursives nous a permis deconfronter la théorie à la réalité des données. Constatant que la SDRT ne rendait pas compte dela diversité des relations causales présentes dans les textes, nous proposons denrichir lemodèle à partir de nos observations. Pour la suite de nos analyses, nous envisageons délargirnotre corpus de façon à le rendre plus représentatif

La ressource EXPLICADIS, un corpus annoté spécifiquement pour l’étude des relations de discours causales

National audienceIn order to offer a characterization of causal discourse relations, we created and annotated our own corpus: EXPLICADIS (EXPlanation and Argumentation in DIScourse). This corpus was built in the continuity of a readily available corpus, the ANNODIS corpus. Providing a more precise annotation of causal relations in a set of texts that are representative of multiple textual genres, EXPLICADIS is the first corpus of its kind built specifically for causal discourse relations studies.Dans le but de proposer une caractérisation des relations de discours liées à la causalité, nous avons été amenée à constituer et annoter notre propre corpus d’étude : la ressource EXPLICADIS (EXPlication et Argumentation en DIScours). Cette ressource a été construite dans la continuité d’une ressource déjà disponible, le corpus ANNODIS. Proposant une annotation plus précise des relations causales sur un ensemble de textes diversifiés en genres textuels, EXPLICADIS est le premier corpus de ce type constitué spécifiquement pour l’étude des relations de discours causales

Analyse de relations de discours causales en corpus : étude empirique et caractérisation théorique

The purpose of this thesis is to study the linguistic realizations of causal relations, according to a semantic and pragmatic approach of discourse structure. Even though causality is a central phenomenon in most theoretical frameworks on discourse, to date there is no consensus on the relations associated to it. Confronting the hypotheses put forward in the literature with our own observations on the basis of attested data, we offer to enrich a specific discourse theoretical model, i.e. SDRT (Segmented Discourse Representation Theory). Therefore, this study stands at the interface between corpus linguistics and theoretical linguistics. The analyses we carried out are based on the EXPLICADIS corpus, which is a written French corpus built specifically to meet the objective. Annotating this corpus with causal discourse relations allowed us to analyze these using an original approach which consists in starting from the relation itself rather than its markers. This approach provided us with the opportunity to offer a unified vision of causality by characterizing the different discourse causal relations in the framework of SDRT. It also provided us with the opportunity to conduct quantitative and comparative corpus studies. Our work also includes an overview of the different means of expression of causality that are documented in written French.Dans cette thèse, nous nous interrogeons sur les réalisations linguistiques des relations causales selon une approche sémantique et pragmatique du discours. Bien que la causalité occupe une place centrale dans les théories du discours, il n’existe pas de consensus quant aux relations qui lui sont associées. Confrontant les propositions faites dans la littérature avec nos observations sur des données attestées, nous proposons de contribuer à l’enrichissement d’une théorie du discours spécifique : la SDRT (Segmented Discourse Representation Theory). Cette thèse se situe donc à l’interface entre linguistique de corpus et linguistique théorique. Les analyses qui y sont menées s’appuient sur le corpus EXPLICADIS, corpus de français écrit constitué spécifiquement pour répondre à l’objectif visé. L’annotation de ce corpus en relations de discours causales nous a ainsi autorisée à procéder à l’analyse de ces relations selon une approche originale qui consiste à prendre pour point de départ la relation elle-même et non ses marqueurs. Cette approche nous a permis d’offrir une vision unificatrice de la causalité en caractérisant les relations de discours qui lui sont liées dans le cadre théorique de la SDRT. Elle nous a également permis de mener des études quantitatives et comparatives sur corpus. Notre travail dresse, en outre, un panorama des moyens d’expression de la causalité observés à l’écrit en français

Discourse Contribution of Enumerative Structures involving "pour deux raisons"

International audienceIn this article, we propose to study the discourse contribution of enumerative structures involving the prepositional phrase pour deux raisons. We would like to highlight the contribution of the textual information conveyed by enumerative structures and the prepositional phrase both to the discourse structure and the discourse content within the SDRT model. We will show that prepositional phrase like pour deux raisons must introduce a discourse constituent in the structure attached by the Commentary relation to the left context and the Enumeration relation to the right context. Finally we propose to treat pour deux raisons as a new kind of discourse marker: we will show that its discursive role within enumerative structures is to signal the content-level relation Explanation

Long-term outcomes of endoscopic sinus surgery for chronic rhinosinusitis with and without nasal polyps

Chronic rhinosinusitis (CRS) significantly affects patient quality of life. Medical and surgical treatments aim to clinically manage the condition. OBJECTIVE: To assess the long-term quality of life and clinical management of CRS in patients submitted to endoscopic sinus surgery. METHOD: This prospective cross-sectional cohort study enrolled 38 patients and looked into the follow-up data of subjects diagnosed with CRS before surgery, three months after surgery, and at least two years after surgery. The Sinonasal Outcome Test 22 (SNOT-22) was used to assess response to treatment and long-term clinical management of the disease. RESULTS: Significant improvements in the SNOT-22 scores were seen between the preoperative (61.3) and postoperative assessments with three (16.9) and 24 (32.3) months. No statistically significant differences were seen when patients with polyps were compared to polyp-free subjects. Few patients were controlled in both groups, and 7.89% of the subjects had revision surgery during the study. CONCLUSION: Endoscopic sinus surgery significantly improved the quality of life of patients with chronic rhinosinusitis. Clinical control of the condition was acceptable, with few patients requiring re-operation within two years of the first surgery.Rinossinusite crônica (RSC) afeta significativamente a qualidade de vida e o tratamento clínico e cirúrgico visa apenas seu controle clínico. OBJETIVO: Avaliar a qualidade de vida e o controle clínico da RSC em longo prazo em pacientes submetidos à cirurgia endoscópica nasossinusal. MÉTODO: Estudo observacional longitudinal prospectivo que seguiu pacientes com diagnóstico clínico de RSC no pré-operatório, pós-operatório de 3 meses e depois por no mínimo 2 anos após cirurgia nasossinusal endoscópica com a utilização do questionário Sinonasal Outcome Test 22 (SNOT-22) como principal medida de resposta ao tratamento, além da avaliação do controle clínico a longo prazo. RESULTADOS: Trinta e oito pacientes foram avaliados em todos os intervalos. Houve uma grande melhora dos valores do SNOT-22 entre o pré-operatório (61,3) e o pós-operatório de 3 (16,9) e 24 meses (32,3). Não houve diferença estatisticamente significante entre os pacientes com e sem pólipos nasais. Nota-se pouca proporção de pacientes controlados em ambos os grupos, e 7,89% foram submetidos à cirurgia revisional no período estudado. CONCLUSÃO: A cirurgia endoscópica nasossinusal promoveu importante melhora da qualidade de vida nos pacientes com rinossinusite crônica, atingindo controle clínico aceitável com baixa necessidade de reintervenção cirúrgica, mesmo após dois anos de seguimento pós-operatório.UNIFESP-EPMUNIFESP, EPMSciEL

Drug repurposing prediction for COVID-19 using probabilistic networks and crowdsourced curation

Severe acute respiratory syndrome coronavirus two (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents an unprecedented global health challenge. Consequently, a large amount of research into the disease pathogenesis and potential treatments has been carried out in a short time frame. However, developing novel drugs is a costly and lengthy process, and is unlikely to deliver a timely treatment for the pandemic. Drug repurposing, by contrast, provides an attractive alternative, as existing drugs have already undergone many of the regulatory requirements. In this work we used a combination of network algorithms and human curation to search integrated knowledge graphs, identifying drug repurposing opportunities for COVID-19. We demonstrate the value of this approach, reporting on eight potential repurposing opportunities identified, and discuss how this approach could be incorporated into future studies

Corpus analysis of causal discourse relations : empirical study and theoretical characterization

Dans cette thèse, nous nous interrogeons sur les réalisations linguistiques des relations causales selon une approche sémantique et pragmatique du discours. Bien que la causalité occupe une place centrale dans les théories du discours, il n’existe pas de consensus quant aux relations qui lui sont associées. Confrontant les propositions faites dans la littérature avec nos observations sur des données attestées, nous proposons de contribuer à l’enrichissement d’une théorie du discours spécifique : la SDRT (Segmented Discourse Representation Theory). Cette thèse se situe donc à l’interface entre linguistique de corpus et linguistique théorique. Les analyses qui y sont menées s’appuient sur le corpus EXPLICADIS, corpus de français écrit constitué spécifiquement pour répondre à l’objectif visé. L’annotation de ce corpus en relations de discours causales nous a ainsi autorisée à procéder à l’analyse de ces relations selon une approche originale qui consiste à prendre pour point de départ la relation elle-même et non ses marqueurs. Cette approche nous a permis d’offrir une vision unificatrice de la causalité en caractérisant les relations de discours qui lui sont liées dans le cadre théorique de la SDRT. Elle nous a également permis de mener des études quantitatives et comparatives sur corpus. Notre travail dresse, en outre, un panorama des moyens d’expression de la causalité observés à l’écrit en français.The purpose of this thesis is to study the linguistic realizations of causal relations, according to a semantic and pragmatic approach of discourse structure. Even though causality is a central phenomenon in most theoretical frameworks on discourse, to date there is no consensus on the relations associated to it. Confronting the hypotheses put forward in the literature with our own observations on the basis of attested data, we offer to enrich a specific discourse theoretical model, i.e. SDRT (Segmented Discourse Representation Theory). Therefore, this study stands at the interface between corpus linguistics and theoretical linguistics. The analyses we carried out are based on the EXPLICADIS corpus, which is a written French corpus built specifically to meet the objective. Annotating this corpus with causal discourse relations allowed us to analyze these using an original approach which consists in starting from the relation itself rather than its markers. This approach provided us with the opportunity to offer a unified vision of causality by characterizing the different discourse causal relations in the framework of SDRT. It also provided us with the opportunity to conduct quantitative and comparative corpus studies. Our work also includes an overview of the different means of expression of causality that are documented in written French

Formal characterization of a new set of causal discourse relations

International audienc