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16504 papers
The purpose of this study was to analyze the performance effects of gender and regional dialect on air traffic control statement recall. Sixty-one student volunteers participated in the experiment. Thirty-one participants held a pilot’s license and 30 participants had no flight experience. Each participant listened to one CD with 60 ATC statements each representing a male and female voice and New England, Southern, and General American dialect. Participants were asked to recall exactly what they heard. If the participant could not understand what they heard, they requested a repeat. The participant’s performance was recorded to CD and analyzed. Demographic questionnaires and dialect familiarity ratings were completed and analyzed. Results showed that the best performance was with the male voice compared to the female voice. Results also showed that greater familiarity with a regional dialect will result in better performance when hearing that dialect. Although birth region was not found to have an impact on regional dialect comprehension, the regional dialect a person speaks in helps in comprehension among that dialect. Results also indicate that experience impacts dialect comprehension as the pilot group performed better across all variables than did the novice group.
This paper presents a prosodic phrasing model for Korean to be used in a text-to-speech synthesis (TTS) system. Read text corpora were morpho-syntactically parsed and prosodically labeled following the Penn Korean Treebank (Han, Chunghye, Ko, Eon-Suk, Yi, Heejong, Palmer, M., 2002. Penn Korean Treebank: development and evaluation. In: Proceedings of the 16th Pacific Asian Conference on Language and Computation. Korean Society for Language and Information.) and K-ToBI prosodic labeling conventions (Sun-Ah, J., 2000. K-ToBI (Korean ToBI) labelling conventions. Version 3.1. Available from: URL.), respectively. Decision trees were trained with morpho-syntactic and textual distance features to predict locations of accentual and intonational phrase breaks. Our phrasing model cross-validated on a 300-sentence corpus (6936 words or 21,436 syllables, with an average of 72 syllables or 23 words per sentence) predicted non-breaks with F=92.4% and breaks with F=88.0% (F=72.8% for accentual phrase breaks and F=71.3% for intonational phrase breaks).
This paper discusses an annotation scheme for Korean null pronouns, which were used in annotating three kinds of Korean text corpora including Penn Korean Treebank. In annotating the corpora, null pronouns and their antecedents were marked up for their type and reference, with coreference relation tracked by numeric identifiers. Based on the annotation scheme, an outline of a potential pronoun resolution strategy is also proposed. The resulting dataset of annotated text is rather small at 11,834 words; we hope the null pronoun classification and annotation scheme proposed in this study will serve as a basis in developing a large-scale annotated corpus in the future.
This report presents an approach to enriching flat and robust predicate argument structures with more fine-grained semantic information, extracted from underspecified semantic representations and encoded in Minimal Recursion Semantics (MRS). Such representations are provided by a hand-built HPSG grammar with a wide linguistic coverage. A specific semantic representation, called linked predicate argument structure (LPAS), has been worked out, which describes the explicit embedding relationships among predicate argument structures. LPAS can be used as a generic interface language for integrating semantic representations with different granularities. Some initial experiments have been conducted to convert MRS expressions into LPASs. A simple constraint solver is developed to resolve the underspecified dominance relations between the predicates and their arguments in MRS expressions. LPASs are useful for high-precision information extraction and question answering tasks because of their fine-grained semantic structures. In addition, I have attempted to extend the lexicon of the HPSG English Resource Grammar (ERG) exploiting WordNet and to disambiguate the readings of HPSG parsing with the help of a probabilistic parser, in order to process texts from application domains. Following the presented approach, the HPSG ERG grammar can be used for annotating some standard treebank, e.g., the Penn Treebank, with its fine-grained semantics. In this vein, I point out opportunities for a fruitful cooperation of the HPSG annotated Redwood Treebank and the Penn PropBank. In my current work, I exploit HPSG as an additional knowledge resource for the automatic learning of LPASs from dependency structures.
There are three types of sentences that form all existing natural languages: verbal sentences (e.g."I read the book."),copulative sentences (e.g."The book is on the table."),and existential sentences (e.g."There is a book on the table.").Syntactic and semantic recognition of these sentence types are crucially important in computational linguistics although there has not been any significant work towards this end.This thesis, in an attempt to fill this evident gap, is on identifying and assigning semantic categories of Turkish existential sentences in print.Existential sentences in Turkish are minimally characterized by the two existential particles var, meaning there is/are, and yok, meaning there is/are no.In addition to these most basic meanings, other senses of existential particles are possible, which can be categorized into groups such as case existentials and possession existentials.Our system does shallow semantic parsing in defining the predicate-argument relationships in an existential sentence on a word-byword basis, via utilizing Support Vector Machines, after which it proceeds with the semantic categorization of the whole sentence.For both of these tasks, our system produces promising results, in terms of accuracy and precision/recall, respectively.Part of this research contributes to the annotation of the METU-Sabanc Turkish Treebank with semantic information.
Abstract. Syntactic disambiguators for natural language often use ”Treebank Grammars”: probabilistic grammars which are directly projected from an annotated corpus. In this paper we show that for describing these systems in the framework of Estimation Theory, we must generalize this theory so that it allows for an infinite number of parameters. Embracing this generalization will also bring the justification of statistical smoothing techniques within the scope of Estimation Theory. 1
NLP applications in all domains require more than a formal grammar to process the input in a practical way, because natural language contains phenomena that a formal grammar is usually not able to describe. Such phenomena are typically disfluencies and extra-grammaticality. Some robust technique is needed to deal with them. An important issue in the development of robust parsing techniques is the choice of flexibility. What precise phenomena outside the systems grammar shall the parser be able to handle? Another question is how to select the correct analysis among the great number of solutions, which are produced as a consequence of the flexibility. This report presents experiments done with two different techniques. One is based on the combination of partial parses, the other on controlled relaxation of grammar rules. In both techniques the selection of the?best? analysis is done with a statistically based ranking procedure. The grammars and test sentences are extracted from two treebanks, ATIS and Susanne. Experimental results show that the first technique has the advantage of full coverage, while the other has a better accuracy. The best performance is achieved by parsing in three passes, first with the initial grammar, then with the rule-relaxation approach and finally, if still no analysis was found, with combination of partial analyses.
Abstract. An important aspect of discourse understanding and generation involves the recognition and processing of discourse relations. These are conveyed by discourse connectives, i.e., lexical items like because and as a result or implicit connectives expressing an inferred discourse relation. The Penn Discourse TreeBank (PDTB) provides annotations of the argument structure, attribution and semantics of discourse connectives. In this paper, we provide the rationale of the tagset, detailed descriptions of the senses with corpus examples, simple semantic definitions of each type of sense tags as well as informal descriptions of the inferences allowed at each level. 1
Introduction The CorpusEye project (http://corp.hum.sdu.dk ) at the University of Denmark aims at designing and programming an internet based corpus search interface that (1) offers standardised search tools and a unified descriptive formalism across different corpus types and different languages, and (2) allows users to exploit grammatical information in annotated corpora in a user-friendly and menubased way. All corpora in CorpusEye have been annotated with VISL's Constraint Grammar based parsers, in the case of treebanks using an additional PSG module or equivalent (Bick 2003). At the time of writing, the material covers 8 languages and ca. 600 million words.
We describe how simple, commonly understood statistical models, such as statistical dependency parsers, probabilistic context-free grammars, and word-to-word translation models, can be effectively combined into a unified bilingual parser that jointly searches for the best English parse, Korean parse, and word alignment, where these hidden structures all constrain each other. The model used for parsing is completely factored into the two parsers and the TM, allowing separate parameter estimation. We evaluate our bilingual parser on the Penn Korean Treebank and against several baseline systems and show improvements parsing Korean with very limited labeled data. 1
We discuss existing approaches to train LR parsers, which have been used for statistical resolution of structural ambiguity. These approaches are nonoptimal, in the sense that a collection of probability distributions cannot be obtained. In particular, some probability distributions expressible in terms of a context-free grammar cannot be expressed in terms of the LR parser constructed from that grammar, under the restrictions of the existing approaches to training of LR parsers. We present an alternative way of training that is provably optimal, and that allows all probability distributions expressible in the context-free grammar to be carried over to the LR parser. We also demonstrate empirically that this kind of training can be effectively applied on a large treebank.
We describe the automatic conversion of English Penn Treebank (PTB) annotations into Language Neutral Syntax (LNS) (Campbell and Suzuki, 2002a,b). In this paper, we describe LNS and why it is useful, describe the conversion algorithm, present an evaluation of the conversion, and discuss some uses of the converted annotations and the potential for extending the coverage to other languages. The work described here is in the spirit of other automatic re-annotations of PTB trees (e.g. Frank, 2000 and Meyers, 2001), but differs in the nature of the output.
The subject matter of this article concerns objectivity of lexicographic description. Here objectivity is being associated with the names of “functional” places, in D. Le Pesant’s understanding of the term. The author presents principles of the object-oriented description of lexicosemantic data, according to the concept by W. Banyś. Later on, she distinguishes a couple of basic classes of appropries predicates, which are typical for the locative nouns suggested by D. Le Pesant. The elements of the object-oriented approach are confronted with their counterparts in such lexicographic theories as: I. Melczuk and A.K. Zholkovsky’s frames, J. Pustejovsky’s qualia structure system, G. Gross’s object classes and unique beginners from the WordNet lexical database. In the suggested descriptive scheme of entries the author places results of her own analyses concerning descriptions of names of functional places, in this case-buildings.
This paper presents a system for automatically generating discourse structures from written text. The system is divided into two levels: sentence-level and text-level. The sentence-level discourse parser uses syntactic information and cue phrases to segment sentences into elementary discourse units and to generate discourse structures of sentences. At the text-level, constraints about textual adjacency and textual organization are integrated in a beam search in order to generate best discourse structures. The experiments were done with documents from the RST Discourse Treebank. It shows promising results in a reasonable search space compared to the discourse trees generated by human analysts.
In natural language processing a huge amount of structured data is constantly used for the extraction and presentation of grammatical structures in sentences. For example the Chinese Treebank corpus developed at the Institute of Information Science Academia Sinica Taiwan is a semantically annotated corpus that has been used to help parse and study Chinese sentences. In this setting users usually use structured tree patterns instead of keywords to query the corpus.
Investigations of the Canadian quotative system have to this point focused on mainland urban varieties where General Canadian English is considered to be the linguistic norm. The current analysis seeks to expand our understanding of this system by examining quotative usage among young girls in St. John’s, Newfoundland, where the local vernacular differs in significant ways from the national variety. Variationist methodology is employed on a small corpus of St. John’s Youth English (SJYE), revealing notable similarities in the distribution of quotatives as well as the operation of internal constraints across the paradigm between this variety and that of the mainland. At the same time, there is evidence that be like, the most recent of the quotative cohort, has grammaticalized further in SJYE than in General Canadian, raising questions about the routes by which this change is progressing. The results thus situate SJYEwithin the Canadian quotative system while at the same time highlighting the status of Newfoundland English as a unique Canadian variety.
In this paper we address the following questions from our experience of the last two and a half years in developing a large-scale corpus of Arabic text annotated for morphological information, part-of-speech, English gloss, and syntactic structure: (a) How did we 'leapfrog' through the stumbling blocks of both methodology and training in setting up the Penn Arabic Treebank (ATB) annotation? (b) How did we reconcile the Penn Treebank annotation principles and practices with the Modern Standard Arabic (MSA) traditional and more recent grammatical concepts? (c) What are the current issues and nagging problems? (d) What has been achieved and what are our future expectations?
Rating agencies' track record is good in developed countries but poor in emerging economies. Why? Given the almost-monopolistic structure of the industry, we conjecture that agencies might underinvest in information gathering. We propose an indicator quantifying the agencies' effort to gather information and assess whether greater effort affects rating levels. We detect: (i) absolute underinvestment for non-OECD sovereigns (less effort in spite of greater opaqueness); (ii) relative underinvestment for non-OECD firms compared with OECD ones (though the former receive a larger effort, more intense effort boosts firm ratings in non-OECD countries while depressing them in OECD countries).
Among the variety of proposals currently making the dependency perspective on grammar more concrete, there are several treebanks whose annotation exploits some form of Relational Structure that we can consider a generalization of the fundamental idea of dependency at various degrees and with reference to different types of linguistic knowledge. The paper describes the Relational Structure as the common underlying representation of treebanks which is motivated by both theoretical and task-dependent considerations. Then it presents a system for the annotation of the Relational Structure in treebanks, called Augmented Relational Structure, which allows for a systematic annotation of various components of linguistic knowledge crucial in several tasks. Finally, it shows a dependency-based annotation for an Italian treebank, i.e. the Turin University Treebank, that implements the Augmented Relational Structure. 1
The present research investigated the hypotheses that elderly people can be reminders of our mortality and that concerns about our own mortality can therefore instigate ageism. In Study 1, college-age participants who saw photos of two elderly people subsequently showed more death accessibility than participants who saw photos of only younger people. In Study 2, making mortality salient for participants increased distancing from the average elderly person and decreased perceptions that the average elderly person possesses favorable attitudes. Mortality salience did not affect ratings of teenagers. In Study 3, these mortality salience effects were moderated by prior reported similarity to elderly people. Distancing from, and derogation of, elderly people after mortality salience occurred only in participants who, weeks before the study, rated their personalities as relatively similar to the average elderly person's. Discussion addresses distinguishing ageism from other forms of prejudice, as well as possibilities for reducing ageism.
Scaling wide-coverage, constraint-based grammars such as Lexical-Functional Grammars (LFG) (Kaplan and Bresnan, 1982; Bresnan, 2001) or Head-Driven Phrase Structure Grammars (HPSG) (Pollard and Sag, 1994) from fragments to naturally occurring unrestricted text is knowledge-intensive, time-consuming and (often prohibitively) expensive. A number of researchers have recently presented methods to automatically acquire wide-coverage, probabilistic constraint-based grammatical resources from treebanks (Cahill et al., 2002, Cahill et al., 2003; Cahill et al., 2004; Miyao et al., 2003; Miyao et al., 2004; Hockenmaier and Steedman, 2002; Hockenmaier, 2003), addressing the knowledge acquisition bottleneck in constraint-based grammar development. Research to date has concentrated on English and German. In this paper we report on an experiment to induce wide-coverage, probabilistic LFG grammatical and lexical resources for Chinese from the Penn Chinese Treebank (CTB) (Xue et al., 2002) based on an automatic f-structure annotation algorithm. Currently 96.751% of the CTB trees receive a single, covering and connected f-structure, 0.112% do not receive an f-structure due to feature clashes, while 3.137% are associated with multiple f-structure fragments. From the f-structure-annotated CTB we extract a total of 12975 lexical entries with 20 distinct subcategorisation frame types. Of these 3436 are verbal entries with a total of 11 different frame types. We extract a number of PCFG-based LFG approximations. Currently our best automatically induced grammars achieve an f-score of 81.57% against the trees in unseen articles 301-325; 86.06% f-score (all grammatical functions) and 73.98% (preds-only) against the dependencies derived from the f-structures automatically generated for the original trees in 301-325 and 82.79% (all grammatical functions) and 67.74% (preds-only) against the dependencies derived from the manually annotated gold-standard f-structures for 50 trees randomly selected from articles 301-325.
Word-to-word dependency structures are useful for consistent representation and comparable evaluation of parsing results. However, most large-scale treebanks contain various variants of phrase structure trees, since automatic parsers usually produce constituent struc-tures. We present a freely available extensible tool for converting phrase structure to dependencies automatically, and discuss its appli-cation to the NEGRA treebank of German. 1.
Nous décrivons l’extraction d’une grammaire d’arbres adjoints (TAG) à partir d’une banque d’arbres de l’arabe écrit. Nous montrons queleques exemples d’arbres élémentaires ainsi obtenus, et les structures de dérivation (donc, de dépendence syntaxique) qui y correspondent. We describe the extraction of a Tree Adjoining Grammar from the Penn Arabic Treebank.1 We show some examples of extracted trees for different constructions, and the corresponding derivation structures (which represent syntactic dependency). 1
This paper describes a method for conducting evaluations of Treebank and non-Treebank parsers alike against the English language U. Penn Treebank (Marcus et al., 1993) using a metric that focuses on the accuracy of relatively non-controversial aspects of parse structure. Our conjecture is that if we focus on maximal projections of heads (MPH), we are likely to find much broader agreement than if we try to evaluate based on order of attachment. We hope that this method may find wider acceptance and be useful in establishing a generally applicable framework for evaluation in natural language parsing. We employ this method in an evaluation of NLPWin (Heidorn, 2000), a parser developed at Microsoft Research without reference to the Penn Treebank, and, for comparison, the well-known statistical Treebank parser of Charniak (2000). 1.
This paper reports on an ongoing project that uses varied language resources and advanced NLP tools for a linguistic classification task in discourse semantics. The system we present is designed to assign a “situation entity ” class label to each predicator in English text. The project goal is to achieve the best-possible identification of situation entities in naturally-occurring written texts by implementing a robust system that will deal with real corpus material, rather than just with constructed textbook examples of discourse. In this paper we focus on the combination of multiple information sources, which we see as being vital for a robust classification system. We use a deep syntactic grammar of English to identify morphological, syntactic, and discourse clues, and we use various lexical databases for fine-grained semantic properties of the predicators. Experiments performed to date show that enhancing the output of the grammar with information from lexical resources improves recall but lowers precision in the situation entity classification task. 1.
The OmniPaper project has implemented several information retrieval prototypes in the area of electronic news publishing. One prototype uses SOAP as communication protocol between the central system and a number of distributed news archives. The second prototype uses an RDF metadata database, enabling direct metadata queries to the central system. Finally the Topic Map prototype uses query expansion and semantic linking for smart metadata search. The Topic Map prototype enhances the search experience by implementing a knowledge layer that combines the semantic content of a lexical database, consisting of concepts and keywords, with a metadata-set of newspaper articles. After developing and testing three smaller prototypes, the OmniPaper consortium has combined these prototypes in one. In this final prototype a kind of “enhanced full-text search” engine is implemented. This means that the prototype is an interface on top of existing search engines. When a user submits a query, this query is forwarded to several distributed news archives to retrieve relevant news articles. Next to this, the system: 1) translates queries to enable multilingual search, 2) provides a query refinement mechanism, both in graphic and text-based form, allowing users to adapt their query and 3) provides uniform result ranking algorithm across the different news archives. In this prototype querying and navigation are considered as alternative methods to find relevant information. Both interact with each other and together they produce a combined user experience that can be expressed as find what you were looking for and then browse away from it. In fact, the prototype considers both querying and navigation as a kind of search action and tries to integrate both. In concrete, keywords in a query are looked up in a dictionary and shown to the user. In the background, the keywords are translated and expanded to related terms. These expanded queries are sent to the underlying full-text search engine(s) in all requested languages. In the graphical tool (“web of concepts”) users can redefine the meaning of their query words, resulting in an updated query and result set. Both disambiguation (choosing one meaning of a word out of many) and refinement (browsing to related words) are possible. Figure 1 shows the web of concepts for the query “poll Indonesia”. The word “Indonesia” is recognized in only one concept, “Dutch East Indies”, whereas the word “poll” has many different meanings. If you select the meaning “canvass” for example, this word is replacing the word “poll” in the original query. After selection the concept “canvass” can again be expanded to related concepts, be it more general or more specific in meaning. In the textual tool only refinement is possible. The user gets a list of words that are related to the words appearing in the query, grouped into more similar, more specific and more general terms. Then the user can change his/her query using these proposed words.
In this paper we present a methodology for extracting subcategorisation frames based on an automatic LFG f-structure annotation algorithm for the Penn-II Treebank. We extract abstract syntactic function-based subcategorisation frames (LFG semantic forms), traditional CFG category-based subcategorisation frames as well as mixed function/category-based frames, with or without preposition information for obliques and particle information for particle verbs. Our approach does not predefine frames, associates probabilities with frames conditional on the lemma, distinguishes between active and passive frames, and fully reflects the effects of long-distance dependencies in the source data structures. We extract 3586 verb lemmas, 14348 semantic form types (an average of 4 per lemma) with 577 frame types. We present a large-scale evaluation of the complete set of forms extracted against the full COMLEX resource.
Relapse is a central problem in smoking treatment. Data collected at the time of relapse episodes indicate that stress and negative affect (NA) promote relapse, but retrospective data are potentially biased. The authors performed a prospective analysis of stress and NA prior to initial lapses in smokers (N = 215). Day-to-day changes in stress (daily negative and positive events and Perceived Stress Scale scores) and NA (multiple momentary affect ratings) did not predict lapse risk on the following day. However, within the lapse day itself, NA was already significantly increasing hours before lapses, but only for episodes attributed to stress or bad mood. Thus, rapid increases in NA, but not slow-changing shifts in stress and NA, were associated with relapse.
In the present paper we discuss some issues connected with the condition of projectivity in a dependency based description of language (see Sgall, Hajičová, and Panevová (1986), Hajičová, Partee, and Sgall (1998)), with a special regard to the annotation scheme of the Prague Dependency Treebank (PDT, see Hajič (1998)). After a short Introduction (Section 1), the condition of projectivity is discussed in more detail in Section 2, presenting its formal definition and formulating an algorithm for testing this condition on a subtree (Section 2.1); the introduction of the condition of projectivity in a formal description of language is briefly substantiated in Section 2.2. and some problematic cases are discussed in Section 2.3. In Section 3, a preliminary classification into three main groups and several subgroups of Czech non-projective constructions on the analytical level is presented (Section 3.1),
How visual cues reveal animacy and social meaning to moving displays is an open question. We investigated this question using techniques of computer vision and image processing that enable full video displays of human action to be decomposed and subsequently transformed into abstract representations of the movement. Using the multimedia analysis program Eyesweb (Infomus lab, U. Genoa), we created visual displays of the same interaction between two dancers performing a modern dance. Four conditions were created that reduced the visual information available. These were: (1) full video recording; (2) body silhouettes; (3) motion of the center of each dancer represented by a single small block changing size in accordance with the motion energy of the dancer; (4) motion of the center of the dancer represented by a single small block that did not change size. Using a between subjects design, participants viewed a two-minute display of a single condition. While viewing, they were asked to provide a continuous measurement of arousal by moving a slider up and down. After this they were asked to write a description of what they had seen. Average arousal ratings were obtained for each condition and analysis revealed higher average ratings of arousal for the full video and silhouette conditions. The free response data was analyzed for spontaneous mention of terms relating to animacy of the display elements. These results indicated that animacy terms were used for the full video and silhouette conditions but not the block conditions. The results are discussed in relation to previous methods used to create stimuli resulting in the attribution of animacy and social meaning to abstract displays of motion.
Recent performance appraisal research has highlighted the important role played by contextual and individual factors in shaping rating behavior. This article reviews cumulated empirical data supporting the proposition that in factors and constraints present in the organization, contexts in which appraisal systems reside and rater attributes, such as personality factors or beliefs, systematically affect rating behavior. The effects of these context and rater factors are reflected in ratings accuracy, ratings discrimination among raters/dimensions, and rating elevation.
The claim made in this paper is that in a formal description of language, it is possible and useful to work with dependency-based underlying representations of sentences (tectogrammatical representations) meeting the condition of projectivity. The reasons for the inclusion of this condition into the definition of the tectogrammatical representations are both formally and empirically sound (Section 1). An analysis of the material offered by the Prague Dependency Treebank with annotations of the underlying syntactic structure of sentences (described in Section 2) has led to an interesting classification of non-projective constructions in Czech (Section 3). It documents that most (types of) constructions that appear to be non-projective in the surface shape of sentences can be described by means of projective trees. The realization of the surface word order (with the use of movement rules) is then relegated to the morphemic level, where the representation of the sentence has the shape of a string rather than a tree.
The annotation of the Prague Dependency Treebank (PDT) is conceived of as a multilayered scenario that comprises also dependency representations (tectogrammatical tree structures, TGTS’s) of the underlying structure of the sentences. TGTS’s capture three basic aspects of the underlying structure of sentences: (a) the dependency tree structure, (b) the kinds of dependency syntactic relations, and (c) the basic characteristics of the topic-focus articulation (TFA). Since the PDT is a large collection and the annotations on the deepest layer are to a large extent performed by several human annotators (based on an automatic preprocessing module), it is more than necessary to observe the consistence of annotators and the agreement among them. In the present paper, we summarize the results of the evaluation of parallel annotations of several samples taken from PDT and the measures accepted to improve the consistency of annotations.
This paper describes and evaluates log-linear parsing models for Combinatory Categorial Grammar (CCG). A parallel implementation of the L-BFGS optimisation algorithm is described, which runs on a Beowulf cluster allowing the complete Penn Treebank to be used for estimation. We also develop a new efficient parsing algorithm for CCG which maximises expected recall of dependencies. We compare models which use all CCG derivations, including non-standard derivations, with normal-form models. The performances of the two models are comparable and the results are competitive with existing wide-coverage CCG parsers.
This paper describes Japanese-English-Chinese aligned parallel treebank corpora of newspaper articles. They have been constructed by translating each sentence in the Penn Treebank and the Kyoto University text corpus into a corresponding natural sentence in a target language. Each sentence is translated so as to reflect its contextual information and is annotated with morphological and syntactic structures and phrasal alignment. This paper also describes the possible applications of the parallel corpus and proposes a new framework to aid in translation. In this framework, parallel translations whose source language sentence is similar to a given sentence can be semi-automatically generated. In this paper we show that the framework can be achieved by using our aligned parallel treebank corpus.
This paper surveys work on applying the insights of lexicalized grammars to low-level discourse, to show the value of positing an autonomous grammar for low-level discourse in which words (or idiomatic phrases) are associated with discourse-level predicate–argument structures or modification structures that convey their syntactic-semantic meaning and scope. It starts by describing a lexicalized Tree Adjoining Grammar for discourse (D-LTAG). It then reviews an initial experiment in parsing text automatically, using both a lexicalized TAG and D-LTAG, and then touches upon issues involved in how lexico-syntactic elements contribute to discourse semantics. The paper concludes with a brief description of the Penn Discourse TreeBank, a resource being developed for the study of discourse structure and semantics.
In two separate studies, we examined fifth graders' preference for authentic and arranged versions of world music recordings, the relationship of those preference ratings to familiarity, and teachers' ability to predict student preferences. In the first study, intact classes of fifth-grade students were randomly assigned to an authentic or arranged listening condition and indicated their familiarity and preference for the same 19 world music songs on a 6-point Likert scale. Teachers of the students in the study attempted to predict their students' preference and familiarity ratings for those same 19 recordings. In the second study, students heard both versions of each song side by side and were asked to first choose the version they preferred, then indicate strength of preference and familiarity. Results of both studies indicated that familiarity with a world music song is positively related to student preference for that song. Subjects in the first study did not differ significantly in the magnitude of their preference ratings between authentic or arranged conditions, whereas subjects in the second study overwhelmingly preferred arranged versions in head-to-head comparisons. Teachers' predictions of preference and familiarity ratings were significantly related to student ratings, though tended to be significantly higher. July 1, 2004 October 20, 2004.
In the design of a Multilingual Lexical Database, one of the biggest problems is constituted by conceptual mismatches between languages, and the resulting matter of lexical gaps. Lexical gaps concern words for which there is no direct translation in a target language, but which nonetheless need to receive a translation within the system. In this article, it will be shown that the various possible ways of dealing with these lexical gaps can be classified in four basic groups. Using the SIM<it>u</it>LLDA system as an example (Janssen 2002), the advantages of the structured interlingua approach over the other possibilities will be explained. With the SIM<it>u</it>LLDA set-up, it is possible to derive correct lexical definitions for lexical gaps from the lexical database. How this process of “lexical gap filling” works will be shown using a concrete example of a lexical gap: the treatment of the English words <it>river</it> and <it>stream </it>in contrast with the French words <it>fleuve</it> and <it>rivière</it>.
The epidemic of mesothelioma in Cappadocia, Turkey, is unprecedented in medical history. In three Cappadocian villages, Karain, Tuzkoy and "old" Sarihidir, about 50% of all deaths (including neonatal deaths and traffic fatalities) have been caused by mesothelioma. No other epidemic in medical history has caused such a high incidence of death. This is even more unusual when considering that (I) epidemics are caused by infectious agents, not cancer, and (II) mesothelioma is a rare cancer. World-wide mesothelioma incidence varies between 1/10<sup>6</sup> in areas with no asbestos industry to about 10-30/10<sup>6</sup> in areas with asbestos industry. This article reviews how the mesothelioma epidemic was discovered in Cappadocia by Dr. Baris (my mentor), how we initially linked the epidemic to erionite exposure, and later (with Dr. Carbone) to the interaction between genetic predisposition and environmental exposure. Our team's work had an important positive impact on the lives of those living in Cappadocia and also in many genetically predisposed families living around the world. I will discuss how the work that started in three remote Cappadocian villages led to the award of a NCI P01 grant to support our studies. Our studies proved that genetics modulates mineral fiber carcinogenesis and led to the discovery that carriers of germline <i>BAP1</i> mutations have a very high risk of developing mesothelioma and other malignancies. A new, very active field of research developed following our discoveries to elucidate the mechanism by which <i>BAP1</i> modulates mineral fiber carcinogenesis as well as to identify additional genes that when mutated increase the risk of mesothelioma and other environmentally related cancers. I am the only surviving member of this research team who saw all the phases of this research and I believe it is important to provide an accurate report, which hopefully will inspire others.
Despite much research, the distinctive personality characteristics of entrepreneurs are yet to be established and the influence of personality on entrepreneurial behaviour remains unclear. This is particularly evident in our understanding of the personal response of entrepreneurs to business failure. In this thesis the Life Story Model of Identity proposed by McAdams' (1993; McAdams & Pals, 2006) narrative theory of personality formed the main theoretical approach to investigating these two related aspects in the psychological understanding of entrepreneurs. This model overcomes some of the limitations of previous personality research by permitting investigation of personality within the entrepreneurial environment and provides a wholistic and complex view of personality as expressed in the entrepreneurs' own words. The model's qualitative methodology and theoretical emphasis on personal meaning making also rendered it most suitable for exploring entrepreneurs' personal response to business failure. McAdams' (1993; McAdams & Pals, 2006) Life Story Interview was employed to explore the self-narrative identities of 40 highly successful entrepreneurs (39 males, one female). Participants were managing directors of businesses sourced from two lists of the fastest growing small to medium companies in Australia, as compiled by the Australian business magazine, the 'Business Review Weekly'. Participants were the founders of their businesses, and had been pursuing entrepreneurship for at least five years. A broad range of business sectors were represented, including computer services, manufacturing, engineering and communications. Prior to interviews, participants completed the Life Story Interview Questionnaire (LSIQ), which was an adapted form of the Life Story Interview that requested written responses to open-ended questions about the content of participants' life stories. A section requesting affective ratings for key events, derived from Herman’s (Hermans & Hermans-Jansen, 1995) Extended List of Affect Terms, was included to further the exploration of life story themes. A second questionnaire, comprised of measures of personality and a measure of psychological symptoms was also completed. During interviews, participants' responses to the LSIQ were discussed, concentrating on further investigation of the key events that defined their life stories. Findings revealed a prototypical life story of the entrepreneur, highlighting distinctive, commonly shared personality characteristics, with much of their selfnarrative identity grounded in experiences within the entrepreneurial environment. The prototypical life story contained a core theme with an agentic-type emphasis on strengthening the self, and a lesser theme with a communion-type emphasis on valuing relationships. Each of these themes comprised two further themes. The selfstrengthening theme included a redemptive theme of overcoming difficulties in a way that left the protagonist feeling stronger and more able to influence their environment, and a positively toned theme of drawing strength and confidence in one's abilities from achievements and successes. The relational theme included a redemptive theme of responding to private relationship difficulties and losses in one area by strengthening other private relationships, and a negatively toned, sometimes contaminated theme, of experiencing either private or professional relational difficulties and losses as irresolvable. The resulting prototypical life story of the entrepreneur was a story centred upon overcoming adversity and celebrating personal achievement, of confirming and boosting confidence in one’s abilities and a sense of personal power to influence their environment. Running parallel to this main storyline was a less prominent plot involving the importance of relationships, with difficulties and losses sometimes redeemed and sometimes left unresolved. To investigate the impact of business failure, participants were asked to describe their experience of business failure as a key life story event during the Life Story Interview. Additional open-ended questions explored important elements of their critical and retrospective responses. A commonly shared personal response was evidenced. Despite being strongly identified with their business at the time, the failure was evaluated in business rather than personal terms. The causes were most often attributed to a combination of internal and external factors, but business recovery was attributed exclusively to their own actions. The self-narrative meanings given to this event centred upon overcoming the business failure in a self-strengthening way as either: mastering business conflict situations; learning entrepreneurial skills; or affirming entrepreneurial self-confidence. In the midst of the failure, most entrepreneurs remained highly optimistic about their chances of success in the future, based largely upon confidence in their ability to bring about business recovery. Practised coping skills were used to manage negative feelings arising from the failure, and an active problem-solving approach was adopted. When reflecting upon their experience, there was an absence of rumination and regret about the business failure. Instead, it was regarded as an inevitable and even welcome event that provided valuable entrepreneurial learning. In making sense of the failure in relation to the rest of their self-narrative identity, most entrepreneurs were able to integrate its meaning within their larger self-story. This was done by relating the business’ recovery to a story of overcoming obstacles, or by containing the business’ failure within a story of either repeated success or sustained self-confidence in one's ability. It was concluded that these entrepreneurs shared a particular type of selfnarrative identity that was conducive to the pursuit of entrepreneurship; positively influencing their behaviour within the entrepreneurial environment and having particular relevance to how they personally responded to business failure. These findings advance understanding of the personality of entrepreneurs, and begin to inform what constitutes a constructive personal response to the event of business failure.
We present a new methodology for the semiautomated maintenance of a treebank built from analyses of a computational grammar and gauge the effort required for each update cycle. Based on a decade of large-scale grammar engineering experience, we propose a tight integration of treebank maintenance with the continuous evolution of a ‘deep’ computational grammar.