The usefulness of phonological information for the acquisition of grammatical structure in child language development

During the process of language development, one of the most important tasks that children must face is that of identifying the grammatical category to which words in their language belong. This is essential in order to be able to form grammatically correct utterances. How do children proceed in order to classify words in their language and assign them to their corresponding grammatical category? The present study investigates the usefulness of phonological information for the categorization of nouns in English, given the fact that it is phonology the first source of information that might be available to prelinguistic infants who lack access to semantic information or complex morphosyntactic information. We analyse four different corpora containing linguistic samples of English speaking mothers addressing their children in order to explore the reliability with which words are represented in mothers’ speech based on several phonological criteria. The results of the analysis confirm the prediction that most of the words to which English learning infants are exposed during the first two years of life can be accounted for in terms of their phonological resemblance

Motion event cognition and grammatical aspect: evidence from Afrikaans

Research on the relationship between grammatical aspect and motion event construal has posited that speakers of non-aspect languages are more prone to encoding event endpoints than are speakers of aspect languages (e.g., von Stutterheim and Carroll 2011). In the present study, we test this hypothesis by extending this line of inquiry to Afrikaans, a non-aspect language which is previously unexplored in this regard. Motion endpoint behavior among Afrikaans speakers was measured by means of a linguistic retelling task and a non-linguistic similarity judgment task, and then compared with the behavior of speakers of a non-aspect language (Swedish) and speakers of an aspect language (English). Results showed the Afrikaans speakers' endpoint patterns aligned with Swedish patterns, but were significantly different from English patterns. It was also found that the variation among the Afrikaans speakers could be partially explained by taking into account their frequency of use of English, such that those who used English more frequently exhibited an endpoint behavior that was more similar to English speakers. The current study thus lends further support to the hypothesis that speakers of different languages attend differently to event endpoints as a function of the grammatical category of aspect.

Colocaciones léxicas en dicconarios monolingües generales del español

El objetivo de la presente investigación es analizar el tratamiento que algunos de los diccionarios generales monolingües del español aparecidos en los últimos diez años han dado al fenómeno de las colocaciones léxicas, a saber, aquellas combinaciones de palabras que, desde el punto de vista de la norma, presentan ciertas restricciones combinatorias, esencialmente de carácter semántico, impuestas por el uso (Corpas: 1996). Los repertorios objeto de análisis han sido: el "Diccionario Salamanca de la lengua española", dirigido por Juan Gutiérrez (1996); el "Diccionario del español actual", de Manuel Seco, Olimpia Andrés y Gabino Ramos (1999); la vigésima segunda edición del diccionario de la RAE (2001); y el "Gran diccionario de uso del español actual. Basado en el corpus Cumbre", dirigido por Aquilino Sánchez (2001). Nuestro estudio se ha fundamentado en un corpus de 52 colocaciones léxicas confeccionado a partir del análisis de las subentradas contenidas en la letra "b" de cada uno de los diccionarios seleccionados. Posteriormente, hemos examinado las entradas correspondientes a cada uno de los elementos que constituyen la colocación (base y colocativo) con el fin de observar si los diccionarios estudiados dan cuenta de estas mismas combinaciones en otras partes del artículo lexicográfico, como son las definiciones o los ejemplos. A la hora de analizar la información lexicográfica hemos centrado nuestra atención en cuatro aspectos: a) la información contenida en las páginas preliminares de cada una de las obras; b) la ubicación de las colocaciones en el artículo lexicográfico; c) la asignación de la colocación a un artículo determinado; y d) la marcación gramatical.

Facilitatory and interfering effects of neighbourhood density on speech production: Evidence from aphasic errors.

In a system where tens of thousands of words are made up of a limited number of phonemes, many words are bound to sound alike. This similarity of the words in the lexicon as characterized by phonological neighbourhood density (PhND) has been shown to affect speed and accuracy of word comprehension and production. Whereas there is a consensus about the interfering nature of neighbourhood effects in comprehension, the language production literature offers a more contradictory picture with mainly facilitatory but also interfering effects reported on word production. Here we report both of these two types of effects in the same study. Multiple regression mixed models analyses were conducted on PhND effects on errors produced in a naming task by a group of 21 participants with aphasia. These participants produced more formal errors (interfering effect) for words in dense phonological neighbourhoods, but produced fewer nonwords and semantic errors (a facilitatory effect) with increasing density. In order to investigate the nature of these opposite effects of PhND, we further analysed a subset of formal errors and nonword errors by distinguishing errors differing on a single phoneme from the target (corresponding to the definition of phonological neighbours) from those differing on two or more phonemes. This analysis confirmed that only formal errors that were phonological neighbours of the target increased in dense neighbourhoods, while all other errors decreased. Based on additional observations favouring a lexical origin of these formal errors (they exceeded the probability of producing a real-word error by chance, were of a higher frequency, and preserved the grammatical category of the targets), we suggest that the interfering effect of PhND is due to competition between lexical neighbours and target words in dense neighbourhoods.

Les erreurs syntaxiques des élèves du secondaire au Québec : analyse de corpus

Ce mémoire de maitrise vise à dresser un portrait des erreurs syntaxiques des élèves du secondaire en analysant un corpus de textes de cinq groupes du Québec, de la 1re à la 5e secondaire. Les résultats actuels aux épreuves ministérielles des élèves de 5e secondaire nous indiquent que les élèves éprouvent des difficultés avec l’écriture du français. Une analyse approfondie nous permet de comprendre que l’amélioration de la situation passe par une meilleure connaissance des erreurs syntaxiques des élèves. En nous appuyant sur la grille de Boivin et Pinsonneault (2014), nous avons analysé les données provenant du codage des textes d’élèves de la 1re à la 5e secondaire. L’analyse de ces données nous a permis de constater que parmi les sept grandes catégories d’erreurs de la grille, c’est en syntaxe que les élèves commettent le plus d’erreurs. Une incursion au cœur des six sous-catégories de la syntaxe a révélé que la ponctuation causait le plus de problème aux élèves, et ce, à tous les niveaux. Les erreurs liées à la détermination de la catégorie grammaticale des mots (homophones) arrivaient en deuxième place. Par la suite, nous avons précisé davantage l’analyse en déterminant, pour chacun des codes, l’évolution du nombre d’erreurs d’un niveau du secondaire à l’autre. Il est ressorti de cette étude que les deux principales erreurs, basées sur les sous-catégories syntaxiques, sont celles portant sur l’usage de la virgule et celles liées à la confusion qui existe encore un verbe terminant par «er» et un adjectif ou un participe passé terminant par «é-e-s».

Las funciones del pasado en los sistemas verbales del español y del ruso

This monograph is a comparative study of past time reference in Spanish and Russian.The ambition is to present a functional perspective of how both languages systemically express temporal and aspectual information. The verb, naturally, attracts the main attention of the thesis and the focus is almost exclusively on verbs in the indicative mood.The definition of the parameters of Time and Aspect plays an important part in the present dissertation. A particular emphasis concerns the elaboration and testing of the ‘ABC’ model, which represents a graphic definition of verbal aspect as a grammatical category.Another important issue is the distinction of aspect and Aktionsart; these concepts are closely related but operate on different functional levels. The analysis is essentially based on linguistic material from parallel corpora, constructed for this purpose. At first the material is treated statistically in order to create astarting point for the qualitative part of the analysis. The three main areas of investigation dealt with are:1) The relation between the simple past tenses, pretérito and imperfecto, in Spanish and their imperfective and perfective counterparts in Russian.2) The relation between the compound tenses in Spanish and the Russian verbal system.The analysis of this relation also comprises a critique of the traditional interpretationof the aspectual contents of the compound tenses.3) The usage of alternative strategies in both languages. In this part of the analysis the focus is widened to include verbal periphrasis, infinite verb forms and subordination. The results of the analysis demonstrate that verbal aspect, according to the definition represented by ‘the ABC model’, works as a grammatical category in both Spanish and Russian. It is also shown that there are systemic differences in the manifestation of this functional category in both languages. Another important result is that the neither the compound tenses nor the progressive express verbal aspect, at least not in a narrow sense of the word but represent different verbal functions related to aspect.

Terminologia de contratos de locação de imóveis: estudo terminológico bilíngue e elaboração de glossário Português-Francês

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Integração das estruturas de complementação oracional no português brasileiro

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estudo exploratório de alterações na linguagem em pacientes com Alzheimer em indivíduos com baixa escolaridade

O presente trabalho descreve características da linguagem, em especial de alguns dos aspectos discursivos, de idosos com envelhecimento saudável, com declínio cognitivo senil, ou com doença de Alzheimer leve e moderada. Foram avaliados um total de 44 idosos sendo 22 saudáveis, 4 com declínio cognitivo senil, 9 com doença de Alzheimer leve e 9 com doença de Alzheimer moderada, classificados pelos critérios do CDR. Foram aplicados os testes neuropsicológicos do mini exame do estado mental, nomeação de Boston resumido, fluência verbal e narrativa por confronto visual (figura do roubo dos bolinhos). Foram estimados os desempenhos nos testes selecionados e aplicada a avaliação dos relatos pelos critérios propostos por Groves-Wright (2004) assim como foi feita a tipificação da narrativa. Tratamento estatístico paramétrico determinou os valores de média, erro-padrão e o nível de significância das diferenças entre as médias foi fixado para valores de p<0.05. Em seguida foi realizado inventário e análise do léxico e das categorias gramaticas das narrativas, e realizada análise paramétrica a partir dos escores Z, através do programa STABLEX. Encontrou-se que a fluência verbal semântica é melhor nos idosos saudáveis quando comparados aos com declínio cognitivo leve. As narrativas mostraram diferenças estatisticamente significantes entre os idosos saudáveis e os com declínio cognitivo leve nas análises de frequência de uso do vocabulário e das categorias gramaticais como um todo, e também entre saudáveis e todos os demais grupos nas análises de cada uma das categorias gramaticais. A análise do vocabulário e das categorias gramaticais permitiu identificar comprometimentos da função narrativa medida pelo tipo de vocabulário e pelas categorias gramaticais preferidas ou rejeitadas. Os resultados contribuem para distinguir as características da narrativa de idosos saudáveis, daquelas de idosos com declínio cognitivo leve ou com Alzheimer leve ou moderado, apontando alterações que possivelmente são indicadores precoces que podem ser usados para avaliar o curso temporal da doença.

O estatuto lexical das preposições sob e sobre

This paper describes the prepositions sob and sobre in the Functional Discourse Grammar framework (HENGEVELD; MACKENZIE, 2008) aiming at checking their lexical or grammatical status on the basis of classification criteria postulated by Keizer (2007). The following aspects point to their lexical status : (i) they consist of an Ascription Subact; (ii) they contain a specific content on the vertical axis signaling inferiority and superiority position in relation to a limit; (iii) they are not required by any predicate, but they are predicates by themselves, which require complementation by an argument playing Reference semantic function; (iv) they may be combined with de, em, para and por; which are genuine grammatical prepositions; and, finally, (v) they are not subjected to any phonological process of reduction and fusion.

Estrutura informacional e clivagem: análise da veiculação de informação em construções clivadas do português brasileiro contemporâneo escrito

Pós-graduação em Linguística e Língua Portuguesa - FCLAR

Name your favorite musician: Effects of masculine generics and of their alternatives in German

Feminist linguists claim that masculine forms used in a generic sense (e.g. he referring to a doctor irrespective of sex) facilitate the cognitive representation of men compared to women and make women less visible. A number of experimental studies have confirmed this assumption with regard to the English language. Concerning other languages, however, this question has been addressed only in very few studies, although gender is a much more pervasive grammatical category and masculine generics are more prominent in languages such as French, Spanish or German. This paper reports three experiments with native speakers of German which were conducted to determine the influence of different types of German generics on the cognitive inclusion of women. Results indicate that inclusion of women is higher with 'non-sexist' alternatives than with masculine generics, a tendency which was consistent over studies. But the different alternative forms show different effects which also vary depending on the context. These results are discussed with regard to their practical consequences in situations such as nominating women and men for awards, political offices etc.

Code-switching: a touchstone of models of bilingual language production

The goal of the present thesis was to investigate the production of code-switched utterances in bilinguals’ speech production. This study investigates the availability of grammatical-category information during bilingual language processing. The specific aim is to examine the processes involved in the production of Persian-English bilingual compound verbs (BCVs). A bilingual compound verb is formed when the nominal constituent of a compound verb is replaced by an item from the other language. In the present cases of BCVs the nominal constituents are replaced by a verb from the other language. The main question addressed is how a lexical element corresponding to a verb node can be placed in a slot that corresponds to a noun lemma. This study also investigates how the production of BCVs might be captured within a model of BCVs and how such a model may be integrated within incremental network models of speech production. In the present study, both naturalistic and experimental data were used to investigate the processes involved in the production of BCVs. In the first part of the present study, I collected 2298 minutes of a popular Iranian TV program and found 962 code-switched utterances. In 83 (8%) of the switched cases, insertions occurred within the Persian compound verb structure, hence, resulting in BCVs. As to the second part of my work, a picture-word interference experiment was conducted. This study addressed whether in the case of the production of Persian-English BCVs, English verbs compete with the corresponding Persian compound verbs as a whole, or whether English verbs compete with the nominal constituents of Persian compound verbs only. Persian-English bilinguals named pictures depicting actions in 4 conditions in Persian (L1). In condition 1, participants named pictures of action using the whole Persian compound verb in the context of its English equivalent distractor verb. In condition 2, only the nominal constituent was produced in the presence of the light verb of the target Persian compound verb and in the context of a semantically closely related English distractor verb. In condition 3, the whole Persian compound verb was produced in the context of a semantically unrelated English distractor verb. In condition 4, only the nominal constituent was produced in the presence of the light verb of the target Persian compound verb and in the context of a semantically unrelated English distractor verb. The main effect of linguistic unit was significant by participants and items. Naming latencies were longer in the nominal linguistic unit compared to the compound verb (CV) linguistic unit. That is, participants were slower to produce the nominal constituent of compound verbs in the context of a semantically closely related English distractor verb compared to producing the whole compound verbs in the context of a semantically closely related English distractor verb. The three-way interaction between version of the experiment (CV and nominal versions), linguistic unit (nominal and CV linguistic units), and relation (semantically related and unrelated distractor words) was significant by participants. In both versions, naming latencies were longer in the semantically related nominal linguistic unit compared to the response latencies in the semantically related CV linguistic unit. In both versions, naming latencies were longer in the semantically related nominal linguistic unit compared to response latencies in the semantically unrelated nominal linguistic unit. Both the analysis of the naturalistic data and the results of the experiment revealed that in the case of the production of the nominal constituent of BCVs, a verb from the other language may compete with a noun from the base language, suggesting that grammatical category does not necessarily provide a constraint on lexical access during the production of the nominal constituent of BCVs. There was a minimal context in condition 2 (the nominal linguistic unit) in which the nominal constituent was produced in the presence of its corresponding light verb. The results suggest that generating words within a context may not guarantee that the effect of grammatical class becomes available. A model is proposed in order to characterize the processes involved in the production of BCVs. Implications for models of bilingual language production are discussed.

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web

OntoTag - A Linguistic and Ontological Annotation Model Suitable for the Semantic Web 1. INTRODUCTION. LINGUISTIC TOOLS AND ANNOTATIONS: THEIR LIGHTS AND SHADOWS Computational Linguistics is already a consolidated research area. It builds upon the results of other two major ones, namely Linguistics and Computer Science and Engineering, and it aims at developing computational models of human language (or natural language, as it is termed in this area). Possibly, its most well-known applications are the different tools developed so far for processing human language, such as machine translation systems and speech recognizers or dictation programs. These tools for processing human language are commonly referred to as linguistic tools. Apart from the examples mentioned above, there are also other types of linguistic tools that perhaps are not so well-known, but on which most of the other applications of Computational Linguistics are built. These other types of linguistic tools comprise POS taggers, natural language parsers and semantic taggers, amongst others. All of them can be termed linguistic annotation tools. Linguistic annotation tools are important assets. In fact, POS and semantic taggers (and, to a lesser extent, also natural language parsers) have become critical resources for the computer applications that process natural language. Hence, any computer application that has to analyse a text automatically and ‘intelligently’ will include at least a module for POS tagging. The more an application needs to ‘understand’ the meaning of the text it processes, the more linguistic tools and/or modules it will incorporate and integrate. However, linguistic annotation tools have still some limitations, which can be summarised as follows: 1. Normally, they perform annotations only at a certain linguistic level (that is, Morphology, Syntax, Semantics, etc.). 2. They usually introduce a certain rate of errors and ambiguities when tagging. This error rate ranges from 10 percent up to 50 percent of the units annotated for unrestricted, general texts. 3. Their annotations are most frequently formulated in terms of an annotation schema designed and implemented ad hoc. A priori, it seems that the interoperation and the integration of several linguistic tools into an appropriate software architecture could most likely solve the limitations stated in (1). Besides, integrating several linguistic annotation tools and making them interoperate could also minimise the limitation stated in (2). Nevertheless, in the latter case, all these tools should produce annotations for a common level, which would have to be combined in order to correct their corresponding errors and inaccuracies. Yet, the limitation stated in (3) prevents both types of integration and interoperation from being easily achieved. In addition, most high-level annotation tools rely on other lower-level annotation tools and their outputs to generate their own ones. For example, sense-tagging tools (operating at the semantic level) often use POS taggers (operating at a lower level, i.e., the morphosyntactic) to identify the grammatical category of the word or lexical unit they are annotating. Accordingly, if a faulty or inaccurate low-level annotation tool is to be used by other higher-level one in its process, the errors and inaccuracies of the former should be minimised in advance. Otherwise, these errors and inaccuracies would be transferred to (and even magnified in) the annotations of the high-level annotation tool. Therefore, it would be quite useful to find a way to (i) correct or, at least, reduce the errors and the inaccuracies of lower-level linguistic tools; (ii) unify the annotation schemas of different linguistic annotation tools or, more generally speaking, make these tools (as well as their annotations) interoperate. Clearly, solving (i) and (ii) should ease the automatic annotation of web pages by means of linguistic tools, and their transformation into Semantic Web pages (Berners-Lee, Hendler and Lassila, 2001). Yet, as stated above, (ii) is a type of interoperability problem. There again, ontologies (Gruber, 1993; Borst, 1997) have been successfully applied thus far to solve several interoperability problems. Hence, ontologies should help solve also the problems and limitations of linguistic annotation tools aforementioned. Thus, to summarise, the main aim of the present work was to combine somehow these separated approaches, mechanisms and tools for annotation from Linguistics and Ontological Engineering (and the Semantic Web) in a sort of hybrid (linguistic and ontological) annotation model, suitable for both areas. This hybrid (semantic) annotation model should (a) benefit from the advances, models, techniques, mechanisms and tools of these two areas; (b) minimise (and even solve, when possible) some of the problems found in each of them; and (c) be suitable for the Semantic Web. The concrete goals that helped attain this aim are presented in the following section. 2. GOALS OF THE PRESENT WORK As mentioned above, the main goal of this work was to specify a hybrid (that is, linguistically-motivated and ontology-based) model of annotation suitable for the Semantic Web (i.e. it had to produce a semantic annotation of web page contents). This entailed that the tags included in the annotations of the model had to (1) represent linguistic concepts (or linguistic categories, as they are termed in ISO/DCR (2008)), in order for this model to be linguistically-motivated; (2) be ontological terms (i.e., use an ontological vocabulary), in order for the model to be ontology-based; and (3) be structured (linked) as a collection of ontology-based triples, as in the usual Semantic Web languages (namely RDF(S) and OWL), in order for the model to be considered suitable for the Semantic Web. Besides, to be useful for the Semantic Web, this model should provide a way to automate the annotation of web pages. As for the present work, this requirement involved reusing the linguistic annotation tools purchased by the OEG research group (http://www.oeg-upm.net), but solving beforehand (or, at least, minimising) some of their limitations. Therefore, this model had to minimise these limitations by means of the integration of several linguistic annotation tools into a common architecture. Since this integration required the interoperation of tools and their annotations, ontologies were proposed as the main technological component to make them effectively interoperate. From the very beginning, it seemed that the formalisation of the elements and the knowledge underlying linguistic annotations within an appropriate set of ontologies would be a great step forward towards the formulation of such a model (henceforth referred to as OntoTag). Obviously, first, to combine the results of the linguistic annotation tools that operated at the same level, their annotation schemas had to be unified (or, preferably, standardised) in advance. This entailed the unification (id. standardisation) of their tags (both their representation and their meaning), and their format or syntax. Second, to merge the results of the linguistic annotation tools operating at different levels, their respective annotation schemas had to be (a) made interoperable and (b) integrated. And third, in order for the resulting annotations to suit the Semantic Web, they had to be specified by means of an ontology-based vocabulary, and structured by means of ontology-based triples, as hinted above. Therefore, a new annotation scheme had to be devised, based both on ontologies and on this type of triples, which allowed for the combination and the integration of the annotations of any set of linguistic annotation tools. This annotation scheme was considered a fundamental part of the model proposed here, and its development was, accordingly, another major objective of the present work. All these goals, aims and objectives could be re-stated more clearly as follows: Goal 1: Development of a set of ontologies for the formalisation of the linguistic knowledge relating linguistic annotation. Sub-goal 1.1: Ontological formalisation of the EAGLES (1996a; 1996b) de facto standards for morphosyntactic and syntactic annotation, in a way that helps respect the triple structure recommended for annotations in these works (which is isomorphic to the triple structures used in the context of the Semantic Web). Sub-goal 1.2: Incorporation into this preliminary ontological formalisation of other existing standards and standard proposals relating the levels mentioned above, such as those currently under development within ISO/TC 37 (the ISO Technical Committee dealing with Terminology, which deals also with linguistic resources and annotations). Sub-goal 1.3: Generalisation and extension of the recommendations in EAGLES (1996a; 1996b) and ISO/TC 37 to the semantic level, for which no ISO/TC 37 standards have been developed yet. Sub-goal 1.4: Ontological formalisation of the generalisations and/or extensions obtained in the previous sub-goal as generalisations and/or extensions of the corresponding ontology (or ontologies). Sub-goal 1.5: Ontological formalisation of the knowledge required to link, combine and unite the knowledge represented in the previously developed ontology (or ontologies). Goal 2: Development of OntoTag’s annotation scheme, a standard-based abstract scheme for the hybrid (linguistically-motivated and ontological-based) annotation of texts. Sub-goal 2.1: Development of the standard-based morphosyntactic annotation level of OntoTag’s scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996a) and also the recommendations included in the ISO/MAF (2008) standard draft. Sub-goal 2.2: Development of the standard-based syntactic annotation level of the hybrid abstract scheme. This level should include, and possibly extend, the recommendations of EAGLES (1996b) and the ISO/SynAF (2010) standard draft. Sub-goal 2.3: Development of the standard-based semantic annotation level of OntoTag’s (abstract) scheme. Sub-goal 2.4: Development of the mechanisms for a convenient integration of the three annotation levels already mentioned. These mechanisms should take into account the recommendations included in the ISO/LAF (2009) standard draft. Goal 3: Design of OntoTag’s (abstract) annotation architecture, an abstract architecture for the hybrid (semantic) annotation of texts (i) that facilitates the integration and interoperation of different linguistic annotation tools, and (ii) whose results comply with OntoTag’s annotation scheme. Sub-goal 3.1: Specification of the decanting processes that allow for the classification and separation, according to their corresponding levels, of the results of the linguistic tools annotating at several different levels. Sub-goal 3.2: Specification of the standardisation processes that allow (a) complying with the standardisation requirements of OntoTag’s annotation scheme, as well as (b) combining the results of those linguistic tools that share some level of annotation. Sub-goal 3.3: Specification of the merging processes that allow for the combination of the output annotations and the interoperation of those linguistic tools that share some level of annotation. Sub-goal 3.4: Specification of the merge processes that allow for the integration of the results and the interoperation of those tools performing their annotations at different levels. Goal 4: Generation of OntoTagger’s schema, a concrete instance of OntoTag’s abstract scheme for a concrete set of linguistic annotations. These linguistic annotations result from the tools and the resources available in the research group, namely • Bitext’s DataLexica (http://www.bitext.com/EN/datalexica.asp), • LACELL’s (POS) tagger (http://www.um.es/grupos/grupo-lacell/quees.php), • Connexor’s FDG (http://www.connexor.eu/technology/machinese/glossary/fdg/), and • EuroWordNet (Vossen et al., 1998). This schema should help evaluate OntoTag’s underlying hypotheses, stated below. Consequently, it should implement, at least, those levels of the abstract scheme dealing with the annotations of the set of tools considered in this implementation. This includes the morphosyntactic, the syntactic and the semantic levels. Goal 5: Implementation of OntoTagger’s configuration, a concrete instance of OntoTag’s abstract architecture for this set of linguistic tools and annotations. This configuration (1) had to use the schema generated in the previous goal; and (2) should help support or refute the hypotheses of this work as well (see the next section). Sub-goal 5.1: Implementation of the decanting processes that facilitate the classification and separation of the results of those linguistic resources that provide annotations at several different levels (on the one hand, LACELL’s tagger operates at the morphosyntactic level and, minimally, also at the semantic level; on the other hand, FDG operates at the morphosyntactic and the syntactic levels and, minimally, at the semantic level as well). Sub-goal 5.2: Implementation of the standardisation processes that allow (i) specifying the results of those linguistic tools that share some level of annotation according to the requirements of OntoTagger’s schema, as well as (ii) combining these shared level results. In particular, all the tools selected perform morphosyntactic annotations and they had to be conveniently combined by means of these processes. Sub-goal 5.3: Implementation of the merging processes that allow for the combination (and possibly the improvement) of the annotations and the interoperation of the tools that share some level of annotation (in particular, those relating the morphosyntactic level, as in the previous sub-goal). Sub-goal 5.4: Implementation of the merging processes that allow for the integration of the different standardised and combined annotations aforementioned, relating all the levels considered. Sub-goal 5.5: Improvement of the semantic level of this configuration by adding a named entity recognition, (sub-)classification and annotation subsystem, which also uses the named entities annotated to populate a domain ontology, in order to provide a concrete application of the present work in the two areas involved (the Semantic Web and Corpus Linguistics). 3. MAIN RESULTS: ASSESSMENT OF ONTOTAG’S UNDERLYING HYPOTHESES The model developed in the present thesis tries to shed some light on (i) whether linguistic annotation tools can effectively interoperate; (ii) whether their results can be combined and integrated; and, if they can, (iii) how they can, respectively, interoperate and be combined and integrated. Accordingly, several hypotheses had to be supported (or rejected) by the development of the OntoTag model and OntoTagger (its implementation). The hypotheses underlying OntoTag are surveyed below. Only one of the hypotheses (H.6) was rejected; the other five could be confirmed. H.1 The annotations of different levels (or layers) can be integrated into a sort of overall, comprehensive, multilayer and multilevel annotation, so that their elements can complement and refer to each other. • CONFIRMED by the development of: o OntoTag’s annotation scheme, o OntoTag’s annotation architecture, o OntoTagger’s (XML, RDF, OWL) annotation schemas, o OntoTagger’s configuration. H.2 Tool-dependent annotations can be mapped onto a sort of tool-independent annotations and, thus, can be standardised. • CONFIRMED by means of the standardisation phase incorporated into OntoTag and OntoTagger for the annotations yielded by the tools. H.3 Standardisation should ease: H.3.1: The interoperation of linguistic tools. H.3.2: The comparison, combination (at the same level and layer) and integration (at different levels or layers) of annotations. • H.3 was CONFIRMED by means of the development of OntoTagger’s ontology-based configuration: o Interoperation, comparison, combination and integration of the annotations of three different linguistic tools (Connexor’s FDG, Bitext’s DataLexica and LACELL’s tagger); o Integration of EuroWordNet-based, domain-ontology-based and named entity annotations at the semantic level. o Integration of morphosyntactic, syntactic and semantic annotations. H.4 Ontologies and Semantic Web technologies (can) play a crucial role in the standardisation of linguistic annotations, by providing consensual vocabularies and standardised formats for annotation (e.g., RDF triples). • CONFIRMED by means of the development of OntoTagger’s RDF-triple-based annotation schemas. H.5 The rate of errors introduced by a linguistic tool at a given level, when annotating, can be reduced automatically by contrasting and combining its results with the ones coming from other tools, operating at the same level. However, these other tools might be built following a different technological (stochastic vs. rule-based, for example) or theoretical (dependency vs. HPS-grammar-based, for instance) approach. • CONFIRMED by the results yielded by the evaluation of OntoTagger. H.6 Each linguistic level can be managed and annotated independently. • REJECTED: OntoTagger’s experiments and the dependencies observed among the morphosyntactic annotations, and between them and the syntactic annotations. In fact, Hypothesis H.6 was already rejected when OntoTag’s ontologies were developed. We observed then that several linguistic units stand on an interface between levels, belonging thereby to both of them (such as morphosyntactic units, which belong to both the morphological level and the syntactic level). Therefore, the annotations of these levels overlap and cannot be handled independently when merged into a unique multileveled annotation. 4. OTHER MAIN RESULTS AND CONTRIBUTIONS First, interoperability is a hot topic for both the linguistic annotation community and the whole Computer Science field. The specification (and implementation) of OntoTag’s architecture for the combination and integration of linguistic (annotation) tools and annotations by means of ontologies shows a way to make these different linguistic annotation tools and annotations interoperate in practice. Second, as mentioned above, the elements involved in linguistic annotation were formalised in a set (or network) of ontologies (OntoTag’s linguistic ontologies). • On the one hand, OntoTag’s network of ontologies consists of − The Linguistic Unit Ontology (LUO), which includes a mostly hierarchical formalisation of the different types of linguistic elements (i.e., units) identifiable in a written text; − The Linguistic Attribute Ontology (LAO), which includes also a mostly hierarchical formalisation of the different types of features that characterise the linguistic units included in the LUO; − The Linguistic Value Ontology (LVO), which includes the corresponding formalisation of the different values that the attributes in the LAO can take; − The OIO (OntoTag’s Integration Ontology), which  Includes the knowledge required to link, combine and unite the knowledge represented in the LUO, the LAO and the LVO;  Can be viewed as a knowledge representation ontology that describes the most elementary vocabulary used in the area of annotation. • On the other hand, OntoTag’s ontologies incorporate the knowledge included in the different standards and recommendations for linguistic annotation released so far, such as those developed within the EAGLES and the SIMPLE European projects or by the ISO/TC 37 committee: − As far as morphosyntactic annotations are concerned, OntoTag’s ontologies formalise the terms in the EAGLES (1996a) recommendations and their corresponding terms within the ISO Morphosyntactic Annotation Framework (ISO/MAF, 2008) standard; − As for syntactic annotations, OntoTag’s ontologies incorporate the terms in the EAGLES (1996b) recommendations and their corresponding terms within the ISO Syntactic Annotation Framework (ISO/SynAF, 2010) standard draft; − Regarding semantic annotations, OntoTag’s ontologies generalise and extend the recommendations in EAGLES (1996a; 1996b) and, since no stable standards or standard drafts have been released for semantic annotation by ISO/TC 37 yet, they incorporate the terms in SIMPLE (2000) instead; − The terms coming from all these recommendations and standards were supplemented by those within the ISO Data Category Registry (ISO/DCR, 2008) and also of the ISO Linguistic Annotation Framework (ISO/LAF, 2009) standard draft when developing OntoTag’s ontologies. Third, we showed that the combination of the results of tools annotating at the same level can yield better results (both in precision and in recall) than each tool separately. In particular, 1. OntoTagger clearly outperformed two of the tools integrated into its configuration, namely DataLexica and FDG in all the combination sub-phases in which they overlapped (i.e. POS tagging, lemma annotation and morphological feature annotation). As far as the remaining tool is concerned, i.e. LACELL’s tagger, it was also outperformed by OntoTagger in POS tagging and lemma annotation, and it did not behave better than OntoTagger in the morphological feature annotation layer. 2. As an immediate result, this implies that a) This type of combination architecture configurations can be applied in order to improve significantly the accuracy of linguistic annotations; and b) Concerning the morphosyntactic level, this could be regarded as a way of constructing more robust and more accurate POS tagging systems. Fourth, Semantic Web annotations are usually performed by humans or else by machine learning systems. Both of them leave much to be desired: the former, with respect to their annotation rate; the latter, with respect to their (average) precision and recall. In this work, we showed how linguistic tools can be wrapped in order to annotate automatically Semantic Web pages using ontologies. This entails their fast, robust and accurate semantic annotation. As a way of example, as mentioned in Sub-goal 5.5, we developed a particular OntoTagger module for the recognition, classification and labelling of named entities, according to the MUC and ACE tagsets (Chinchor, 1997; Doddington et al., 2004). These tagsets were further specified by means of a domain ontology, namely the Cinema Named Entities Ontology (CNEO). This module was applied to the automatic annotation of ten different web pages containing cinema reviews (that is, around 5000 words). In addition, the named entities annotated with this module were also labelled as instances (or individuals) of the classes included in the CNEO and, then, were used to populate this domain ontology. • The statistical results obtained from the evaluation of this particular module of OntoTagger can be summarised as follows. On the one hand, as far as recall (R) is concerned, (R.1) the lowest value was 76,40% (for file 7); (R.2) the highest value was 97, 50% (for file 3); and (R.3) the average value was 88,73%. On the other hand, as far as the precision rate (P) is concerned, (P.1) its minimum was 93,75% (for file 4); (R.2) its maximum was 100% (for files 1, 5, 7, 8, 9, and 10); and (R.3) its average value was 98,99%. • These results, which apply to the tasks of named entity annotation and ontology population, are extraordinary good for both of them. They can be explained on the basis of the high accuracy of the annotations provided by OntoTagger at the lower levels (mainly at the morphosyntactic level). However, they should be conveniently qualified, since they might be too domain- and/or language-dependent. It should be further experimented how our approach works in a different domain or a different language, such as French, English, or German. • In any case, the results of this application of Human Language Technologies to Ontology Population (and, accordingly, to Ontological Engineering) seem very promising and encouraging in order for these two areas to collaborate and complement each other in the area of semantic annotation. Fifth, as shown in the State of the Art of this work, there are different approaches and models for the semantic annotation of texts, but all of them focus on a particular view of the semantic level. Clearly, all these approaches and models should be integrated in order to bear a coherent and joint semantic annotation level. OntoTag shows how (i) these semantic annotation layers could be integrated together; and (ii) they could be integrated with the annotations associated to other annotation levels. Sixth, we identified some recommendations, best practices and lessons learned for annotation standardisation, interoperation and merge. They show how standardisation (via ontologies, in this case) enables the combination, integration and interoperation of different linguistic tools and their annotations into a multilayered (or multileveled) linguistic annotation, which is one of the hot topics in the area of Linguistic Annotation. And last but not least, OntoTag’s annotation scheme and OntoTagger’s annotation schemas show a way to formalise and annotate coherently and uniformly the different units and features associated to the different levels and layers of linguistic annotation. This is a great scientific step ahead towards the global standardisation of this area, which is the aim of ISO/TC 37 (in particular, Subcommittee 4, dealing with the standardisation of linguistic annotations and resources).

Portrait des difficultés des élèves du secondaire relativement à l’orthographe des formes homophones

Cette recherche descriptive vise à établir un portrait des principales difficultés rencontrées par les élèves du secondaire relativement à l’orthographe des homophones et cela à travers différents angles d’analyse. Nous avons d’abord fait ressortir l’importance des difficultés orthographiques chez les élèves du secondaire québécois et mis en relief la proportion de ces erreurs attribuée à l’orthographe des homophones. À partir des données recueillies par le groupe de recherche Projet grammaire-écriture qui s’est donné comme objectif, dans un premier temps, de recueillir de nombreuses données à travers deux instruments de collecte (une dictée et une production écrite), nous avons tout d’abord relevé les erreurs d’homophonie commises le plus fréquemment par les élèves pour ensuite analyser chacune des formes homophones problématiques en fonction de critères variés tels que leur fréquence lexicale dans la langue française, leur appartenance à une catégorie grammaticale particulière ou encore la structure syntaxique qui les sous-tend. Les erreurs les plus importantes ont fait l’objet d’une observation plus poussée : nous avons établi le pourcentage de graphies correctes versus erronées dans tous les textes des élèves. Finalement, nous avons aussi comparé nos résultats à ceux obtenus par McNicoll et Roy (1984) auprès d’une population de niveau primaire. Les résultats révélés par notre analyse montrent que ce sont principalement les finales verbales en /E/ qui posent problème aux élèves du secondaire, suivies par les formes homophones s’est/c’est/ces/ses et se/ce.