Another Facet of LIG Parsing (extended version)

In this paper we present a new parsing algorithm for linear indexed grammars (LIGs) in the same spirit as the one described in (Vijay-Shanker et Weir, 1993) for tree adjoining grammars. For a LIG $L$ and an input string $x$ of length $n$, we build a non ambiguous context-free grammar whose sentences are all (and exclusively) valid derivation sequences in $L$ which lead to $x$. We show that this grammar can be built in ${\cal O}(n^6)$ time and that individual parses can be extracted in linear time with the size of the extracted parse tree. Though this ${\cal O}(n^6)$ upper bound does not improve over previous results, the average case behaves much better. Moreover, practical parsing times can be decreased by some statically performed computations

Annotation of morphology and NP structure in the Copenhagen Dependency Treebanks (CDT)

Proceedings of the Ninth International Workshop on Treebanks and Linguistic Theories. Editors: Markus Dickinson, Kaili Müürisep and Marco Passarotti. NEALT Proceedings Series, Vol. 9 (2010), 151-162. © 2010 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/15891

ReaderBench, an Environment for Analyzing Text Complexity and Reading Strategies

Session: Educational Data MiningInternational audienceReaderBench is a multi-purpose, multi-lingual and flexible environment that enables the assessment of a wide range of learners' productions and their manipulation by the teacher. ReaderBench allows the assessment of three main textual features: cohesion-based assessment, reading strategies identification and textual complexity evaluation, which have been subject to empirical validations. ReaderBench covers a complete cycle, from the initial complexity assessment of reading materials, the assignment of texts to learners, the capture of metacognitions reflected in one's textual verbalizations and comprehension evaluation, therefore fostering learner's self-regulation process

On TAG and Multicomponent TAG Parsing

The notion of mild context-sensitivity is an attempt to express the formal power needed to define the syntax of natural languages. However, all incarnati- ons of mildly context-sensitive formalisms are not equivalent. On the one hand, near the bottom of the hierarchy, we find tree adjoining grammars and, on the other hand, near the top of the hierarchy, we find multicomponent tree adjoining grammars. This paper proposes a polynomial parse time method for these two tree rewriting formalisms. This method uses range concatenation grammars as a high-level intermediate definition formalism, and yields several algorithms. Range concatenation grammar is a syntactic formalism which is both powerful, in so far as it extends linear context-free rewriting systems, and efficient, in so far as its sentences can be parsed in polynomial time. We show that any unrestricted tree adjoining grammar can be transformed into an equivalent range concatenation grammar which can be parsed in O(n6) time, and, moreover, if the input tree adjoining grammar has some restricted form, its parse time decreases to O(n5). We generalize one of these algorithms in order to process multicomponent tree adjoining grammars. We show some upper bounds on their parse times, and we introduce a hierarchy of restricted forms which can be parsed more efficiently. Our approach aims at giving both a new insight into the multicomponent adjunction mechanism and at providing a practical implementation scheme

Web services for transcriptomics

Transcriptomics is part of a family of disciplines focussing on high throughput molecular biology experiments. In the case of transcriptomics, scientists study the expression of genes resulting in transcripts. These transcripts can either perform a biological function themselves or function as messenger molecules containing a copy of the genetic code, which can be used by the ribosomes as templates to synthesise proteins. Over the past decade microarray technology has become the dominant technology for performing high throughput gene expression experiments. A microarray contains short sequences (oligos or probes), which are the reverse complement of fragments of the targets (transcripts or sequences derived thereof). When genes are expressed, their transcripts (or sequences derived thereof) can hybridise to these probes. Many thousand copies of a probe are immobilised in a small region on a support. These regions are called spots and a typical microarray contains thousands or sometimes even more than a million spots. When the transcripts (or sequences derived thereof) are fluorescently labelled and it is known which spots are located where on the support, a fluorescent signal in a certain region represents expression of a certain gene. For interpretation of microarray data it is essential to make sure the oligos are specific for their targets. Hence for proper probe design one needs to know all transcripts that may be expressed and how well they can hybridise with candidate oligos. Therefore oligo design requires: 1. A complete reference genome assembly. 2. Complete annotation of the genome to know which parts may be transcribed. 3. Insight in the amount of natural variation in the genomes of different individuals. 4. Knowledge on how experimental conditions influence the ability of probes to hybridise with certain transcripts. Unfortunately such complete information does not exist, but many microarrays were designed based on incomplete data nevertheless. This can lead to a variety of problems including cross-hybridisation (non-specific binding), erroneously annotated and therefore misleading probes, missing probes and orphan probes. Fortunately the amount of information on genes and their transcripts increases rapidly. Therefore, it is possible to improve the reliability of microarray data analysis by regular updates of the probe annotation using updated databases for genomes and their annotation. Several tools have been developed for this purpose, but these either used simplistic annotation strategies or did not support our species and/ or microarray platforms of interest. Therefore, we developed OligoRAP (Oligo Re- Annotation Pipeline), which is described in chapter 2. OligoRAP was designed to take advantage of amongst others annotation provided by Ensembl, which is the largest genome annotation effort in the world. Thereby OligoRAP supports most of the major animal model organisms including farm animals like chicken and cow. In addition to support for our species and array platforms of interest OligoRAP employs a new annotation strategy combining information from genome and transcript databases in a non-redundant way to get the most complete annotation possible. In chapter 3 we compared annotation generated with 3 oligo annotation pipelines including OligoRAP and investigated the effect on functional analysis of a microarray experiment involving chickens infected with Eimeria bacteria. As an example of functional analysis we investigated if up- or downregulated genes were enriched for Terms from the Gene Ontology (GO). We discovered that small differences in annotation strategy could lead to alarmingly large differences in enriched GO terms. Therefore it is important to know, which annotation strategy works best, but it was not possible to assess this due to the lack of a good reference or benchmark dataset. There are a few limited studies investigating the hybridisation potential of imperfect alignments of oligos with potential targets, but in general such data is scarce. In addition it is difficult to compare these studies due to differences in experimental setup including different hybridisation temperatures and different probe lengths. As result we cannot determine exact thresholds for the alignments of oligos with non-targets to prevent cross-hybridisation, but from these different studies we can get an idea of the range for the thresholds that would be required for optimal target specificity. Note that in these studies experimental conditions were first optimised for an optimal signal to noise ratio for hybridisation of oligos with targets. Then these conditions were used to determine the thresholds for alignments of oligos with non-targets to prevent cross-hybridisation. Chapter 4 describes a parameter sweep using OligoRAP to explore hybridisation potential thresholds from a different perspective. Given the mouse genome thresholds were determined for the largest amount of gene specific probes. Using those thresholds we then determined thresholds for optimal signal to noise ratios. Unfortunately the annotation-based thresholds we found did not fall within the range of experimentally determined thresholds; in fact they were not even close. Hence what was experimentally determined to be optimal for the technology was not in sync with what was determined to be optimal for the mouse genome. Further research will be required to determine whether microarray technology can be modified in such a way that it is better suited for gene expression experiments. The requirement of a priori information on possible targets and the lack of sufficient knowledge on how experimental conditions influence hybridisation potential can be considered the Achiles’ heels of microarray technology. Chapter 5 is a collection of 3 application notes describing other tools that can aid in analysis of transcriptomics data. Firstly, RShell, which is a plugin for the Taverna workbench allowing users to execute statistical computations remotely on R-servers. Secondly, MADMAX services, which provide quality control and normalisation of microarray data for AffyMetrix arrays. Finally, GeneIlluminator, which is a tool to disambiguate gene symbols allowing researchers to specifically retrieve literature for their genes of interest even if the gene symbols for those genes had many synonyms and homonyms. Web services High throughput experiments like those performed in transcriptomics usually require subsequent analysis with many different tools to make biological sense of the data. Installing all these tools on a single, local computer and making them compatible so users can build analysis pipelines can be very cumbersome. Therefore distributed analysis strategies have been explored extensively over the past decades. In a distributed system providers offer remote access to tools and data via the Internet allowing users to create pipelines from modules from all over the globe. Chapter 1 provides an overview of the evolution of web services, which represent the latest breed in technology for creating distributed systems. The major advantage of web services over older technology is that web services are programming language independent, Internet communication protocol independent and operating system independent. Therefore web services are very flexible and most of them are firewall-proof. Web services play a major role in the remaining chapters of this thesis: OligoRAP is a workflow entirely made from web services and the tools described in chapter 5 all provide remote programmatic access via web service interfaces. Although web services can be used to build relatively complex workflows like OligoRAP, a lack of mainly de facto standards and of user-friendly clients has limited the use of web services to bioinformaticians. A semantic web where biologists can easily link web services into complex workflows does n <br/

Conversational Browsing

How can we better understand the mechanisms behind multi-turn information seeking dialogues? How can we use these insights to design a dialogue system that does not require explicit query formulation upfront as in question answering? To answer these questions, we collected observations of human participants performing a similar task to obtain inspiration for the system design. Then, we studied the structure of conversations that occurred in these settings and used the resulting insights to develop a grounded theory, design and evaluate a first system prototype. Evaluation results show that our approach is effective and can complement query-based information retrieval approaches. We contribute new insights about information-seeking behavior by analyzing and providing automated support for a type of information-seeking strategy that is effective when the clarity of the information need and familiarity with the collection content are low

Interrelations Among Personality, Religious and Nonreligious Coping, and Mental Health

Religion\u27s involvement in the coping process remains an underexplored area of coping research despite most psychologists agreeing that religion is integral to this process for many individuals. Interestingly, there is some disagreement among psychologists regarding whether religious coping can be reduced to nonreligious coping (Siegel, Anderman, & Schrimshaw, 2001). To better understand how religious and nonreligious coping contribute uniquely to the prediction of mental health outcomes, the study\u27s first and second goals were to determine the incremental validity of each type of coping, above and beyond the other. The study\u27s third goal was to determine whether select coping strategies mediated the relationships between personality and mental health, thereby elucidating the nature of their interrelations. Finally, to further the aim of positive psychology, the current study incorporated positive mental health outcomes into its analyses, as well as negative mental health outcomes. A sample of 300 college students completed a packet of questionnaires that included measures of religious and nonreligious coping strategies, personality, depression, anxiety, stress, hopefulness, quality-of-life, and life satisfaction. Hierarchical multiple regression analyses were used to test the incremental validity of religious and nonreligious coping strategies; whereas structural equation modeling was used to explore whether any of the coping strategies mediated the relationships between personality and mental health. Results suggest that religious and nonreligious coping both provide unique information about mental health outcomes. However, religious and nonreligious coping strategies appear to relate differently to mental health, depending on whether positive or negative outcomes are studied. This finding provides further evidence that a state of flourishing is something different from the mere absence of pathology

Interpretación tabular de autómatas para lenguajes de adjunción de árboles

[Resumen] Las gramáticas de adjunción de árboles son una extensión de las gramáticas independientes del contexto que utilizan árboles en vez de producciones como estructuras elementales y que resultan adecuadas para la descripción de la mayor parte de las construcciones sintácticas presentes en el lenguaje natural. Los lenguajes generados por esta clase de gramáticas se denominan lenguajes de adjunción de árboles y son equivalentes a los lenguajes generados por las gramáticas lineales de índices y otros formalismos suavemente dependientes del contexto. En la primera parte de esta memoria se presenta el problema del análisis sintáctico de los lenguajes de adjunción de árboles. Para ello, se establece un camino evolutivo continuo en el que se sitúan los algoritmos de análisis sintáctico que incorporan las estrategias de análisis más importantes, tanto para el caso de las gramáticas de adjunción de árboles como para el caso de las gramáticas lineales de índices. En la segunda parte se definen diferentes modelos de autómata que aceptan exactamente los lenguajes de adjunción de árboles y se proponen técnicas que permiten su ejecución eficiente. La utilización de autómatas para realizar el análisis sintáctico es interesante porque permite separar el problema de la definición de un algoritmo de análisis sintáctico del problema de la ejecución del mismo, al tiempo que simplifica las pruebas de corrección. Concretamente, hemos estudiado los siguientes modelos de autómata: • Los autómatas a pila embebidos descendentes y ascendentes, dos extensiones de ^ los autómatas a pila que utilizan como estructura de almacenamiento una pila de pilas. Hemos definido nuevas versiones de estos autómatas en las cuales se simplifica la forma de las transiciones y se elimina el control de estado finito, manteniendo la potencia expresiva. • La restricción de los autómatas lógicos a pila para adaptarlos al reconocimiento de las gramáticas lineales de índices, obteniéndose diferentes tipos de autómatas especializados en diversas estrategias de análisis según el conjunto de transiciones permitido. • Los autómatas lineales de índices, tanto los orientados a la derecha, adecuados para estrategias en las cuales las adjunciones se reconocen de manera ascendente, los orientados a la izquierda, aptos para estrategias de análisis en las que las adjunciones se tratan de forma descendente, como los fuertemente dirigidos, capaces de incorporar estrategias de análisis en las cuales las adjunciones se tratan de manera ascendente y/o descendente. • Los autómatas con dos pilas, una extensión de los autómatas a pila que trabaja con una pila maestra encargada de dirigir el proceso de análisis y una pila auxiliar que restringe las transiciones aplicables en un momento dado. Hemos descrito dos versiones diferentes de este tipo de autómatas, los autómatas con dos pilas fuertemente dirigidos, aptos para describir estrategias de análisis arbitrarias, y los autómatas con dos pilas ascendentes, adecuados para describir estrategias de análisis en las cuales las adjunciones se procesan ascendentemente. Hemos definido esquemas de compilación para todos estos modelos de autómata. Estos esquemas permiten obtener el conjunto de transiciones correspondiente a la implantación de una determinada estrategia de análisis sintáctico para una gramática dada. Todos los modelos de autómata pueden ser ejecutados en tiempo polinomial con respecto a la longitud de la cadena de entrada mediante la aplicación de técnicas de interpretación tabular. Estas técnicas se basan en la manipulación de representaciones colapsadas de las configuraciones del autómata, denominadas ítems, que se almacenan en una tabla para su posterior reutilización. Con ello se evita la realización de cálculos redundantes. Finalmente, hemos analizado conjuntamente los diferentes modelos de autómata, los cuales se pueden dividir en tres grandes grupos: la familia de los autómatas generales, de la que forman parte los autómatas lineales de índices fuertemente dirigidos y los autómatas con dos pilas fuertemente dirigidos; la familia de los autómatas descendentes, en la que se encuadran los autómatas a pila embebidos y los autómatas lineales de índices orientados a la izquierda; y la familia de los autómatas ascendentes, en la que se enmarcan los autómatas a pila embebidos ascendentes, los autómatas lineales de índices orientados a la derecha y los autómatas con dos pilas ascendentes.[Abstract] Tree adjoining grammars are an extension of context-free grammars that use trees instead of productions as the primary representing structure and that are considered to be adequate to describe most of syntactic phenomena occurring in natural languages. These grammars generate the class of tree adjoining languages, which is equivalent to the class of languages generated by linear indexed grammars and other mildly context-sensitive formalisms. In the first part of this dissertation, we introduce the problem of parsing tree adjoining grammars and linear indexed grammars, creating, for both formalisms, a continuum from simple pure bottom-up algorithms to complex predictive algorithms and showing what transformations must be applied to each one in order to obtain the next one in the continuum. In the second part, we define several models of automata that accept the class of tree adjoining languages, proposing techniques for their efficient execution. The use of automata for parsing is interesting because they allow us to separate the problem of the definition of parsing algorithms from the problem of their execution. We have considered the following types of automata: • Top-down and bottom-up embedded push-down automata, two extensions of push-down automata working on nested stacks. A new definition is provided in which the finite-state control has been eliminated and several kinds of normalized transition have been defined, preserving the equivalence with tree adjoining languages. • Logical push-down automata restricted to the case of tree adjoining languages. Depending on the set of allowed transitions, we obtain three different types of automata. • Linear indexed automata, left-oriented and right-oriented to describe parsing strategies in which adjuntions are recognized top-down and bottom-up, respectively, and stronglydriven to define parsing strategies recognizing adjunctions top-down and/or bottom-up. • 2-stack automata, an extension of push-down automata working on a pair of stacks, a master stack driving the parsing process and an auxiliary stack restricting the set of transitions that can be applied at a given moment. Strongly-driven 2-stack automata can be used to describe bottom-up, top-down or mixed parsing strategies for tree adjoining languages with respect to the recognition of the adjunctions. Bottom-up 2-stack automata are specifically designed for parsing strategies recognizing adjunctions bottom-up. Compilation schemata for these models of automata have been defined. A compilation schema allow us to obtain the set of transitions corresponding to the implementation of a^ parsing strategy for a given grammar. All the presented automata can be executed in polynomial time with respect to the length of the input string by applying tabulation techniques. A tabular technique makes possible to interpret an automaton by means of the manipulation of collapsed representation of configurations (called items) instead of actual configurations. Items are stored into a table in order to be reused, avoiding redundant computations. Finally, we have studied the relations among the diíferent classes of automata, the main dif%rence being the storage structure used: embedded stacks, indices lists or coupled stacks. According to the strategies that can be implemented, we can distinguish three kinds of automata: bottom-up automata, including bottom-up embedded push-down automata, bottomup restricted logic push-down automata, right-oriented linear indexed automata and bottom-up 2-stack automata; top-down automata, including (top-down) embedded push-down automata, top-down restricted logic push-down automata and left-oriented linear indexed automata; and general automata, including strongly-driven linear indexed automata and strongly-driven 2- stack automata

Proceedings

Proceedings of the Ninth International Workshop on Treebanks and Linguistic Theories. Editors: Markus Dickinson, Kaili Müürisep and Marco Passarotti. NEALT Proceedings Series, Vol. 9 (2010), 268 pages. © 2010 The editors and contributors. Published by Northern European Association for Language Technology (NEALT) http://omilia.uio.no/nealt . Electronically published at Tartu University Library (Estonia) http://hdl.handle.net/10062/15891