On Left and Right Dislocation: A Dynamic Perspective

The paper argues that by modelling the incremental and left-right process of interpretation as a process of growth of logical form (representing logical forms as trees), an integrated typology of left-dislocation and right-dislocation phenomena becomes available, bringing out not merely the similarities between these types of phenomena, but also their asymmetry. The data covered include hanging topic left dislocation, clitic left dislocation, left dislocation, pronoun doubling, expletives, extraposition, and right node raising, with each set of data analysed in terms of general principles of tree growth. In the light of the success in providing a characterisation of the asymmetry between left and right periphery phenomena, a result not achieved in more wellknown formalisms, the paper concludes that grammar formalisms should model the dynamics of language processing in time.Articl

On past participle agreement in transitive clauses in French

This paper provides a Minimalist analysis of past participle agreement in French in transitive clauses. Our account posits that the head v of vP in such structures carries an (accusativeassigning) structural case feature which may apply (with or without concomitant agreement) to case-mark a clause-mate object, the subject of a defective complement clause, or an intermediate copy of a preposed subject in spec-CP. In structures where a goal is extracted from vP (e.g. via wh-movement) v also carries an edge feature, and may also carry a specificity feature and a set of (number and gender) agreement features. We show how these assumptions account for agreement of a participle with a preposed specific clausemate object or defective-clause subject, and for the absence of agreement with an embedded object, with the complement of an impersonal verb, and with the subject of an embedded (finite or nonfinite) CP complement. We also argue that the absence of agreement marking (in expected contexts) on the participles faitmade and laissélet in infinitive structures is essentially viral in nature. Finally, we claim that obligatory participle agreement with reflexive and reciprocal objects arises because the derivation of reflexives involves A-movement and concomitant agreement

Description of the Chinese-to-Spanish rule-based machine translation system developed with a hybrid combination of human annotation and statistical techniques

Two of the most popular Machine Translation (MT) paradigms are rule based (RBMT) and corpus based, which include the statistical systems (SMT). When scarce parallel corpus is available, RBMT becomes particularly attractive. This is the case of the Chinese--Spanish language pair. This article presents the first RBMT system for Chinese to Spanish. We describe a hybrid method for constructing this system taking advantage of available resources such as parallel corpora that are used to extract dictionaries and lexical and structural transfer rules. The final system is freely available online and open source. Although performance lags behind standard SMT systems for an in-domain test set, the results show that the RBMT’s coverage is competitive and it outperforms the SMT system in an out-of-domain test set. This RBMT system is available to the general public, it can be further enhanced, and it opens up the possibility of creating future hybrid MT systems.Peer ReviewedPostprint (author's final draft

The Bantu-Romance-Greek connection revisited: processing constraints in auxiliary and clitic placement from a cross-linguistic perspective

This paper explores a connection between Romance and Greek on the one hand, and Bantu on the other. More specifically, we look at auxiliary placement in Rangi and clitic placement in Tobler Mussafia languages, with a special emphasis on Cypriot Greek, and argue that a common explanation for their distribution can be found once a move into a dynamic framework is made. Rangi exhibits an unusual word order alternation in auxiliary constructions under which the position of the auxiliary appears to be sensitive to an element appearing at the left periphery of the clause. A similar sensitivity to a left-peripheral element can be seen to regulate clitic placement in Cypriot Greek (and generally in the so-called Tobler Mussafia clitic languages). The paper presents a parsing-oriented account of these two phenomena in the Dynamic Syntax framework, arguing that the similarities in syntactic distribution are the result of the encoding in the lexicon of processing strategies that were potentially pragmatic preferences in earlier stages of the respective languages. The account thus leans on the role played by the lexical entries for auxiliary and clitic forms, as well as the assumption that underspecification is inherent in the process of establishing meaning in context. The account is further supplemented by possible pathways of diachronic change that could have given rise to the systems found in present day varieties

Statistical Deep parsing for spanish

This document presents the development of a statistical HPSG parser for Spanish. HPSG is a deep linguistic formalism that combines syntactic and semanticinformation in the same representation, and is capable of elegantly modelingmany linguistic phenomena. Our research consists in the following steps: design of the HPSG grammar, construction of the corpus, implementation of theparsing algorithms, and evaluation of the parsers performance. We created a simple yet powerful HPSG grammar for Spanish that modelsmorphosyntactic information of words, syntactic combinatorial valence, and semantic argument structures in its lexical entries. The grammar uses thirteenvery broad rules for attaching specifiers, complements, modifiers, clitics, relative clauses and punctuation symbols, and for modeling coordinations. In asimplification from standard HPSG, the only type of long range dependency wemodel is the relative clause that modifies a noun phrase, and we use semanticrole labeling as our semantic representation. We transformed the Spanish AnCora corpus using a semi-automatic processand analyzed it using our grammar implementation, creating a Spanish HPSGcorpus of 517,237 words in 17,328 sentences (all of AnCora). We implemented several statistical parsing algorithms and trained them overthis corpus. The implemented strategies are: a bottom-up baseline using bi-lexical comparisons or a multilayer perceptron; a CKY approach that uses theresults of a supertagger; and a top-down approach that encodes word sequencesusing a LSTM network. We evaluated the performance of the implemented parsers and compared them with each other and against other existing Spanish parsers. Our LSTM top-down approach seems to be the best performing parser over our test data, obtaining the highest scores (compared to our strategies and also to externalparsers) according to constituency metrics (87.57 unlabeled F1, 82.06 labeled F1), dependency metrics (91.32 UAS, 88.96 LAS), and SRL (87.68 unlabeled,80.66 labeled), but we must take in consideration that the comparison against the external parsers might be noisy due to the post-processing we needed to do in order to adapt them to our format. We also defined a set of metrics to evaluate the identification of some particular language phenomena, and the LSTM top-down parser out performed the baselines in almost all of these metrics as well.Este documento presenta el desarrollo de un parser HPSG estadístico para el español. HPSG es un formalismo lingüístico profundo que combina información sintáctica y semántica en sus representaciones, y es capaz de modelar elegantemente una buena cantidad de fenómenos lingüísticos. Nuestra investigación se compone de los siguiente pasos: diseño de la gramática HPSG, construcción del corpus, implementación de los algoritmos de parsing y evaluación de la performance de los parsers. Diseñamos una gramática HPSG para el español simple y a la vez poderosa, que modela en sus entradas léxicas la información morfosintáctica de las palabras, la valencia combinatoria sintáctica y la estructura argumental semántica. La gramática utiliza trece reglas genéricas para adjuntar especificadores, complementos, clíticos, cláusulas relativas y símbolos de puntuación, y también para modelar coordinaciones. Como simplificación de la teoría HPSG estándar, el único tipo de dependencia de largo alcance que modelamos son las cláusulas relativas que modifican sintagmas nominales, y utilizamos etiquetado de roles semánticos como representación semántica. Transformamos el corpus AnCora en español utilizando un proceso semiautomático y lo analizamos mediante nuestra implementación de la gramática, para crear un corpus HPSG en español de 517,237 palabras en 17,328 oraciones (todo el contenido de AnCora). Implementamos varios algoritmos de parsing estadístico entrenados sobre este corpus. En particular, teníamos como objetivo probar enfoques basados en redes neuronales. Las estrategias implementadas son: una línea base bottom-up que utiliza comparaciones bi-léxicas o un perceptrón multicapa; un enfoque tipo CKY que utiliza los resultados de un supertagger; y un enfoque top-down que codifica las secuencias de palabras mediante redes tipo LSTM. Evaluamos la performance de los parsers implementados y los comparamos entre sí y con un conjunto de parsers existententes para el español. Nuestro enfoque LSTM top-down parece ser el que tiene mejor desempeño para nuestro conjunto de test, obteniendo los mejores puntajes (comparado con nuestras estrategias y también con parsers externos) en cuanto a métricas de constituyentes (87.57 F1 no etiquetada, 82.06 F1 etiquetada), métricas de dependencias (91.32 UAS, 88.96 LAS), y SRL (87.68 no etiquetada, 80.66 etiquetada), pero debemos tener en cuenta que la comparación con parsers externos puede ser ruidosa debido al post procesamiento realizado para adaptarlos a nuestro formato. También definimos un conjunto de métricas para evaluar la identificación de algunos fenómenos particulares del lenguaje, y el parser LSTM top-down obtuvo mejores resultados que las baselines para casi todas estas métricas

Modeling the Learning of the Person Case Constraint

Many domains of linguistic research posit feature bundles as an explanation for various phenomena. Such hypotheses are often evaluated on their simplicity (or parsimony). We take a complementary approach. Specifically, we evaluate different hypotheses about the representation of person features in syntax on the basis of their implications for learning the Person Case Constraint (PCC). The PCC refers to a phenomenon where certain combinations of clitics (pronominal bound morphemes) are disallowed with ditransitive verbs. We compare a simple theory of the PCC, where person features are represented as atomic units, to a feature-based theory of the PCC, where person features are represented as feature bundles. We use Bayesian modeling to compare these theories, using data based on realistic proportions of clitic combinations from child-directed speech. We find that both theories can learn the target grammar given enough data, but that the feature-based theory requires significantly less data, suggesting that developmental trajectories could provide insight into syntactic representations in this domain