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Political strategists decide daily how to market their candidates. Growing recognition of the importance of implicit processes (processes occurring outside of awareness) suggests limitations to focus groups and polling, which rely on conscious self‐report. Two experiments, inspired by national political campaigns, employed Internet‐presented subliminal primes to study evaluations of politicians. In Experiment 1, the subliminal word “RATS” increased negative ratings of an unknown politician. In Experiment 2, conducted during former California Governor Gray Davis's recall referendum, a subliminal photo of Clinton affected ratings of Davis, primarily among Independents. Results showed that subliminal stimuli can affect ratings of well‐known as well as unknown politicians. Further, subliminal studies can be conducted in a mass media outlet (the Internet) in real time and supplement voter self‐report, supporting the potential utility of implicit measures for campaign decision making.
International audience
The suitability of different parsing methods for different languages is an important topic in syntactic parsing. Especially lesser-studied languages, typologically different from the languages for which methods have originally been developed, pose interesting challenges in this respect. This article presents an investigation of data-driven dependency parsing of Turkish, an agglutinative, free constituent order language that can be seen as the representative of a wider class of languages of similar type. Our investigations show that morphological structure plays an essential role in finding syntactic relations in such a language. In particular, we show that employing sublexical units called inflectional groups, rather than word forms, as the basic parsing units improves parsing accuracy. We test our claim on two different parsing methods, one based on a probabilistic model with beam search and the other based on discriminative classifiers and a deterministic parsing strategy, and show that the usefulness of sublexical units holds regardless of the parsing method. We examine the impact of morphological and lexical information in detail and show that, properly used, this kind of information can improve parsing accuracy substantially. Applying the techniques presented in this article, we achieve the highest reported accuracy for parsing the Turkish Treebank.
A number of researchers have recently conducted experiments comparing “deep” hand-crafted wide-coverage with “shallow” treebank- and machine-learning-based parsers at the level of dependencies, using simple and automatic methods to convert tree output generated by the shallow parsers into dependencies. In this article, we revisit such experiments, this time using sophisticated automatic LFG f-structure annotation methodologies with surprising results. We compare various PCFG and history-based parsers to find a baseline parsing system that fits best into our automatic dependency structure annotation technique. This combined system of syntactic parser and dependency structure annotation is compared to two hand-crafted, deep constraint-based parsers, RASP and XLE. We evaluate using dependency-based gold standards and use the Approximate Randomization Test to test the statistical significance of the results. Our experiments show that machine-learning-based shallow grammars augmented with sophisticated automatic dependency annotation technology outperform hand-crafted, deep, wide-coverage constraint grammars. Currently our best system achieves an f-score of 82.73% against the PARC 700 Dependency Bank, a statistically significant improvement of 2.18% over the most recent results of 80.55% for the hand-crafted LFG grammar and XLE parsing system and an f-score of 80.23% against the CBS 500 Dependency Bank, a statistically significant 3.66% improvement over the 76.57% achieved by the hand-crafted RASP grammar and parsing system.
We present a dependency-driven parser that parses both dependency structures and constituent structures. Constituency representations are automatically transformed into dependency representations with complex arc labels, which makes it possible to recover the constituent structure with both constituent labels and grammatical functions. We report a labeled attachment score close to 90% for dependency versions of the TIGER and TúBa-D/Z treebanks. Moreover, the parser is able to recover both constituent labels and grammatical functions with an F-Score over 75% for TüBa-D/Z and over 65% for TIGER.
Problematic types of prepositions, conjuctions, and particles and possible ways of their treatment in the lexical database.
Traditional Active Learning (AL) techniques assume that the annotation of each datum costs the same. This is not the case when annotating sequences; some sequences will take longer than others. We show that the AL technique which performs best depends on how cost is measured. Applying an hourly cost model based on the results of an annotation user study, we approximate the amount of time necessary to annotate a given sentence. This model allows us to evaluate the effectiveness of AL sampling methods in terms of time spent in annotation. We acheive a 77% reduction in hours from a random baseline to achieve 96.5% tag accuracy on the Penn Treebank. More significantly, we make the case for measuring cost in assessing AL methods.
Abstract Affective ratings of multiple religious (sub)groups (Muslims, Christians, Jews and non-believers, as well as Sunni, Alevi and Sjiit Muslims), the endorsement of Islamic minority rights and religious group identification were examined among Sunni and Alevi Turkish-Dutch participants. The findings show that both groups differ in important ways. Some Alevi participants considered themselves Muslims but others interpreted Alevi identity in a secular way. The Sunnis were quite negative towards Jews and non-believers, they more strongly endorsed Islamic minority rights and they had very high Muslim group identification. Furthermore, the Sunnis were negative towards Alevis and the Alevis were negative towards the Sunnis. Muslim group identification was positively and strongly related to feelings towards Muslims and to the endorsement of Islamic group rights.
In this paper we present the methodology for Word Sense Disambiguation based on domain information. Domain is a set of words in which there is a strong semantic relation among the words. The words in the sentence contribute to determine the domain of the sentence. The availability of WordNet domains makes the domain-oriented text analysis possible. The domain of the target word can be fixed based on the domains of the content words in the local context. This approach can be effectively used to disambiguate nouns. We present the unsupervised approach to Word Sense Disambiguation using the WordNet domains. The model determines the domain of the target word and the sense corresponding to this domain is taken as the correct sense. We have used the WordNet domains 3.1.as lexical database.
Possession in some Austronesian languages shows levels of elaboration far in excess of cross-linguistic norms, while in others it is strikingly unelaborated. The appearance of alienable/inalienable contrasts has been assumed to result from contact with Papuan languages, and the existence of a paradigm of indirect possessive classifiers is cited as one of the pieces of evidence for the Oceanic subgroup, while acknowledging that indirect possession constructions can be found in Malayo-Polynesian languages further west. We argue that the appearance of possessive classifiers in these languages is also the result of contact with Papuan languages west of New Guinea.
Abstract Large linguistic databases, especially databases having a global coverage, such as the World Atlas of Language Structures, the Automated Similarity Judgment Program, and Ethnologue, are making it possible to systematically investigate many aspects of how languages change and compete for viability. Agent‐based computer simulations supplement such empirical data by analyzing the necessary and sufficient parameters for the current global distributions of languages or linguistic features. By combining empirical datasets with simulations and applying quantitative methods, it is now possible to address fundamental questions, such as ‘what are the relative rates of change in different parts of languages?’, ‘why are there a few large language families, many intermediate ones, and even more small ones?’, ‘do small languages change faster or slower than large ones?’, or ‘how does the borrowing of words relate to the borrowing of structural features?’
In this paper the role of concept characteristics in lexical dialectometric research is examined in three consecutive logical steps. First, a regression analysis of data taken from a large lexical database of Limburgish dialects in Belgium and The Netherlands is conducted to illustrate that concept characteristics such as concept salience, concept vagueness and negative affect contribute to the lexical heterogeneity in the dialect data. Next, it is shown that the relationship between concept characteristics and lexical heterogeneity influences the results of conventional lexical dialectometric measurements. Finally, a dialectometric procedure is proposed which downplays this undesired influence, thus making it possible to obtain a clearer picture of the ‘truly’ regional variation. More specifically, a lexical dialectometric method is proposed in which concept characteristics form the basis of a weighting schema that determines to which extent concept specific dissimilarities can contribute to the aggregate dissimilarities between locations.
This paper describes a method of accurately projecting Propbank roles onto constituents in the CCGbank with near perfect accuracy and automatically annotating verbal categories with the semantic roles of their arguments. The current version of the CCGbank annotates arguments and adjuncts in a suboptimal way – it relies heavily on the Penn Treebank CLR tag, which is widely considered unreliable. By incorporating Propbank roles we are able to modify the derivation to better reflect linguistic reality. Tagging of nodes in the CCG derivation also permits us to annotate verbal categories with semantic roles corresponding to their syntactic arguments, which has strong implications for many NLP tasks.
The Berkeley FrameNet Project (BFN) is making an English lexical database called FrameNet, which describes syntactic and semantic properties of an English lexicon extracted from large electronic text corpora (Baker et al., 1998). Other projects dealing with Spanish, German and Japanese follow a similar approach and annotate large corpora. FrameSQL is a web-based application developed by the author, and it allows the user to search the BFN database in a variety of ways (Sato, 2003). FrameSQL shows a clear view of the headword’s grammar and combinatorial properties offered by the FrameNet database. FrameSQL has been developing and new functions were implemented for processing the Spanish FrameNet data (Subirats and Sato, 2004). FrameSQL is also in the process of incorporating the data of the Japanese FrameNet Project (Ohara et al., 2003) and that of the Saarbrücken Lexical Semantics Acquisition Project (Erk et al., 2003) into the database and will offer the same user-interface for searching these lexical data. This paper describes new functions of FrameSQL, showing how FrameSQL deals with the lexical data of English, Spanish, Japanese and German seamlessly. 1.
OBJECTIVE: This experimental, repeated-measures, crossover design study with nursing home residents examined the efficacy of reflexology in individuals with mild-to-moderate stage dementia. Specifically, the study tested whether a weekly reflexology intervention contributed to the resident outcomes of reduced physiologic distress, reduced pain, and improved affect. SETTING: The study was conducted at a large nursing home in suburban Philadelphia. SAMPLE: The sample included 21 nursing home residents with mild-to-moderate stage dementia randomly assigned to two groups. INTERVENTIONS: The first group received 4 weeks of weekly reflexology treatments followed by 4 weeks of a control condition of friendly visits. The second group received 4 weeks of friendly visits followed by 4 weeks of weekly reflexology. OUTCOME MEASURES: The primary efficacy endpoint was reduction of physiologic distress as measured by salivary alpha-amylase. The secondary outcomes were observed pain (Checklist of Nonverbal Pain Indicators) and observed affect (Apparent Affect Rating Scale). RESULTS: The findings demonstrate that when receiving the reflexology treatment condition, as compared to the control condition, the residents demonstrated significant reduction in observed pain and salivary alpha-amylase. No adverse events were recorded during the study period. CONCLUSIONS: This study provides preliminary support for the efficacy of reflexology as a treatment of stress in nursing home residents with mild-to-moderate stage dementia.
Approximately 35% of individuals with dementia exhibit depression and/or anxiety symptoms, often manifested by symptoms of negative affect. Exercise has been associated with improved affect but has not been demonstrated to improve affect in residents of secured dementia units in long-term care facilities. This pilot study determined whether moderate-intensity, chair-based exercise was associated with changes in negative affect in residents in secured units. The sample included 36 patients from 2 nursing homes who participated in a 12-week, 30-minute moderate-intensity group exercise program thrice weekly. Affect, measured by the Philadelphia Geriatric Center Apparent Affect Rating Scale, was assessed at weeks 3 and 12, before and after each exercise session. Paired t tests assessed the immediate effect of exercise (before/after a session) and the long-term effect of exercise (study initiation/12 wk) on patients' affect ratings. The mean age was 85 years (SD=5.5), with 86% female, and 97% white. At week 3, anxiety was significantly lower immediately after the exercise session when adjusted for level of participation (P=0.02) compared with immediately before the exercise session, indicating immediate changes in affect. Anxiety and depression were significantly reduced at week 12, when compared with week 3, after adjusting for level of participation (P=0.01; P=0.03), indicating long-term effects of the exercise intervention. The study revealed the feasibility of conducting a moderate-intensity exercise program and the potential for exercise as a nonpharmacologic intervention for reducing symptoms of negative affect and depression in this vulnerable population.
Recent parsing research has started addressing the questions a) how parsers trained on different syntactic resources differ in their performance and b) how to conduct a meaningful evaluation of the parsing results across such a range of syntactic representations. Two German treebanks, Negra and TüBa-D/Z, constitute an interesting testing ground for such research given that the two treebanks make very different representational choices for this language, which also is of general interest given that German is situated between the extremes of fixed and free word order. We show that previous work comparing PCFG parsing with these two treebanks employed PARSEVAL and grammatical function comparisons which were skewed by differences between the two corpus annotation schemes. Focusing on the grammatical dependency triples as an essential dimension of comparison, we show that the two very distinct corpora result in comparable parsing performance.
In Brief Objectives: Accurate identification of environmental sounds plays an important role in maintaining listeners’ awareness of their environment, and is a major concern for cochlear implant patients. Although research indicates that decreased spectral resolution has a negative effect on environmental sound identification, little is known about the processes underlying perceptual adaptation to spectrally-degraded input. The goals of this study were (1) to develop a test of environmental sound perception containing a large variety of easily identifiable and familiar sound sources, represented by multiple exemplars, and (2) to examine whether auditory training improves listeners’ identification of spectrally-degraded environmental sounds. Design: In experiment 1, familiarity ratings and identification accuracy were obtained for 21 normal-hearing subjects for 48 environmental sound sources; there were 4 exemplars of each sound source, for a total of 192 stimuli. A second test was developed using a subset of 40 sound sources (4 exemplars each, for a total of 160 stimuli). In experiment 2, seven normal-hearing subjects (who did not participate in experiment 1) were asked to identify spectrally-degraded environmental sounds processed by a four-channel noise-band vocoder. The second stimulus set developed in experiment 1 (40 sound sources, 4 exemplars each) was used in experiment 2. The subjects were tested in a pretest–posttest design with five training sessions between the pretest and the posttest. The training sounds were selected individually for each subject, and comprised one half of the sound sources that were misidentified in the pretest. Each sound source used in training was represented by two exemplars. During training, subjects received trial and block feedback. For each incorrect response, subjects were allowed to replay the stimulus up to five times after being shown the correct response. Results: In experiment 1, listeners’ average identification accuracy was 95% correct, with 178 of all sounds identified with an accuracy of 80% or more. The average identification accuracy of the 160 sounds selected for experiment 2 was 98% correct, and their average familiarity rating was 6.39 (on a 7-point scale). In experiment 2, the average identification accuracy of spectrally-degraded sounds was 33% correct on the pretest. However, after training, average identification accuracy across all sounds improved to 63% correct on the posttest. The largest improvement (86 percentage points) was obtained for the sound exemplars used during training. The identification accuracy for alternative exemplars of the training sounds (that referenced the same sources) improved by 36 percentage points. Finally, the identification of sound sources not included in the training, but perceived with equal difficulty on the pretest, improved by 18 percentage points. Conclusions: These results demonstrate positive effects of training on the identification of spectrally-degraded environmental sounds and suggest that training effects can generalize to other sound exemplars and sources, although with a reduced magnitude of improvement. The findings also indicate a timeline for initial perceptual adaptation to spectrally-degraded environmental sounds, and provide a preliminary basis for incorporating environmental sounds into auditory rehabilitation programs for cochlear implant patients. Environmental sound perception is an important concern for cochlear implant patients. In this study, a large 160-item test of environmental sound perception was developed and used to examine whether auditory training improves listeners’ identification of environmental sounds processed by an acoustically simulated cochlear implant. Seven normal-hearing listeners identified spectrally-degraded stimuli obtained with a four-channel noise-based vocoder before and after five training sessions. Identification performance improved after training, mostly for the sounds included in the training set, but also, to a lesser extent, for untrained sounds. Results provide preliminary basis for incorporating environmental sounds into cochlear implant rehabilitation programs.
What’s the best way to assess the performance of a semantic component in an NLP system? Tradition in NLP evaluation tells us that comparing output against a gold standard is a good idea. To define a gold standard, one first needs to decide on the representation language, and in many cases a first-order language seems a good compromise between expressive power and efficiency. Secondly, one needs to decide how to represent the various semantic phenomena, in particular the depth of analysis of quantification, plurals, eventualities, thematic roles, scope, anaphora, presupposition, ellipsis, comparatives, superlatives, tense, aspect, and time-expressions. Hence it will be hard to come up with an annotation scheme unless one permits different level of semantic granularity. The alternative is a theory-neutral black-box type evaluation where we just look at how systems react on various inputs. For this approach, we can consider the well-known task of recognising textual entailment, or the lesser-known task of textual model checking. The disadvantage of black-box methods is that it is difficult to come up with natural data that cover specific semantic phenomena. 1. Evaluating Meaning Formal methods for the analysis of the meaning of natural language expressions have long been restricted to the ivory tower built by semanticists, logicians, and philosophers of language. It was only in exceptional cases that they made their way directly into open domain NLP tools. Recently, this situation has changed. Thanks to the development of treebanks (large collections of texts annotated with syntactic structures), robust statistical parsers trained on such treebanks, and the development of large-scale semantic lexica, we now have at our disposal systems that are able to produce formal semantic representations achieving
High doses of ibuprofen have been shown to inhibit muscle protein synthesis after a bout of resistance exercise. We determined the effect of a moderate dose of ibuprofen (400 mg x d(-1)) consumed on a daily basis after resistance training on muscle hypertrophy and strength. Twelve males and 6 females (approximately 24 years of age) trained their right and left biceps on alternate days (6 sets of 4-10 repetitions), 5 d x week(-1), for 6 weeks. In a counter-balanced, double-blind design, they were randomized to receive 400 mg x d(-1) ibuprofen immediately after training their left or right arm, and a placebo after training the opposite arm the following day. Before- and after-training muscle thickness of both biceps was measured using ultrasound and 1 repetition maximum (1 RM) arm curl strength was determined on both arms. Subjects rated their muscle soreness daily. There were time main effects for muscle thickness and strength (p < 0.01). Ibuprofen consumption had no effect on muscle hypertrophy (muscle thickness of biceps for arm receiving ibuprofen: pre 3.63 +/- 0.14, post 3.92 +/- 0.15 cm; and placebo: pre 3.62 +/- 0.15, post 3.90 +/- 0.15 cm) and strength (1 RM of arm receiving ibuprofen: pre 18.6 +/- 2.8, post 23.4 +/- 3.5 kg; and placebo: pre 18.8 +/- 2.8, post 22.8 +/- 3.4 kg). Muscle soreness was elevated during the first week of training only, but was not different between the ibuprofen and placebo arm. We conclude that a moderate dose of ibuprofen ingested after repeated resistance training sessions does not impair muscle hypertrophy or strength and does not affect ratings of muscle soreness.
German genitive attributes are usually tagged as such in treebanks. However, it is well known that this information is not sufficient for determining the type of relation between head nouns and attributes, as genitive attributes can express many different semantic relations. Various linguistic classifications have been worked out, but to my knowledge, nobody has so far proposed to apply this linguistic knowledge to a corpus. The challenge here is to come up with a classification that is both easy to verify and sufficiently fine-grained. Using earlier linguistic approaches as guidelines, I propose in this paper a detailed annotation scheme for German genitive attributes based on readily identifiable noun features. First insights from its application to the Smultron Treebank show that it is easy to distinguish between the proposed classes and that my classification of genitive attributes can be related to a more general semantic annotation level.
As the first holder of the first chair in computational linguistics in Sweden, Anna Sagvall Hein has played a central role in the development of computational linguistics and language technology bo...
Humans are unique in being able to reflect on their own performance. For example, we are more motivated to do well on a task when we are told that our abilities are being evaluated. We set out to study the effect of self-motivation on a working memory task. By telling one group of participants that we were assessing their cognitive abilities, and another group that we were simply optimizing task parameters, we managed to enhance the motivation to do well in the first group. We matched the performance between the groups. During functional magnetic resonance imaging, the motivated group showed enhanced activity when making errors. This activity was extensive, including the anterior paracingulate cortex, lateral prefrontal and orbitofrontal cortex. These areas showed enhanced interaction with each other. The anterior paracingulate activity correlated with self-image ratings, and overlapped with activity when participants explicitly reflected upon their performance. We suggest that the motivation to do well leads to treating errors as being in conflict with one's ideals for oneself.
This paper proposes an approach using large scale case structures, which are automatically constructed from both a small tagged corpus and a large raw corpus, to improve Chinese dependency parsing. The case structure proposed in this paper has two characteristics: (1) it relaxes the predicate of a case structure to be all types of words which behaves as a head; (2) it is not categorized by semantic roles but marked by the neighboring modifiers attached to a head. Experimental results based on Penn Chinese Treebank show the proposed approach achieved 87.26% on unlabeled attachment score, which significantly outperformed the baseline parser without using case structures.
Recent work in Evolutionary Phonology (Blevins 2005, 2006, Blevins & Wedel 2008, Yu 2007, among others) has developed alternate explanations for typological universals or tendencies found across the sound systems of unrelated languages. This research emphasizes the role of patterns of language use and language change in the development of cross-linguistic patterns, rather than placing the burden of explanation on synchronic cognitive factors (i.e., Universal Grammar).
This paper introduces the infrastructure and the principles of a semantic framework used for the analysis and classification of verbs, developed with the aim of constructing a lexical database of Mandarin verbal semantics, called the Mandarin VerbNet. Distinct from most existing lexical databases that enumerate word senses without detailed grammatical considerations, the Mandarin VerbNet is designed to provide lexical semantic information based on grammatical descriptions and anchored in linguistic theories. It looks for systematic correlations between syntax and semantics and classifies verbs according to these syntax-to-semantics correspondences. The framework adopts the approach of Frame Semantics (Fillmore & Atkins 1992) in defining verb meanings in a semantic frame and building a frame-based verbal lexicon, but it differs from the structure of the English FrameNet in distinguishing different scopes of frames. Evolved and refined from previous works (Liu, Chiang & Chang 2004, Liu & Wu 2003, Liu 2002), this study summarizes the current model of the analytic framework with a detailed illustration from Mandarin statement verbs. It ultimately seeks to identify a theoretically sound and operationally effective representational scheme that bases its semantic analysis on grammatical behaviors and provides linguistic motivations for its semantic classifications.
Creation of material, technical and personal prerequisites for lexicographic work by using modern technologies; information on lexicographical bibliographical database.
Morphologically rich languages pose a challenge to the annotators of treebanks with respect to the status of orthographic (spacedelimited) words in the syntactic parse trees. In such languages an orthographic word may carry various, distinct, sorts of information and the question arises whether we should represent such words as a sequence of their constituent morphemes (i.e., a Morpheme-Based annotation strategy) or whether we should preserve their special orthographic status within the trees (i.e., a Word-Based annotation strategy). In this paper we empirically address this challenge in the context of the development of Language Resources for Modern Hebrew. We compare and contrast the Morpheme-Based and Word-Based annotation strategies of pronominal clitics in Modern Hebrew and we show that the Word-Based strategy is more adequate for the purpose of training statistical parsers as it provides a better PP-attachment disambiguation capacity and a better alignment with initial surface forms. Our findings in turn raise new questions concerning the interaction of morphological and syntactic processing of which investigation is facilitated by the parallel treebank we made available. 1.
Robust spoken language understanding (SLU) is a key component of spoken dialogue systems. Recent statistical approaches to this problem require additional resources (e.g. gazetteers, grammars, syntactic treebanks) which are expensive and time-consuming to produce and maintain. However, simple datasets annotated only with slot-values are commonly used in dialogue systems development, and are easy to collect, automatically annotate, and update. We show that it is possible to reach state-of-the-art performance using minimal additional resources, by using Markov logic networks (MLNs). We also show that performance can be further improved by exploiting long distance dependencies between slot-values. For example, by representing such features in MLNs, but without using a gazetteer, we outperform the hidden vector state (HVS) model of He and Young 2006 (1.26% improvement, a 13% error reduction).
Expression of the serotonin transporter is affected by the genotype of the 5-HTTLPR (short and long forms) as well as the genotype of the SNP rs25531 within this region. Based on the combined genotypes for these polymorphisms, we designated each allele as a high or low expressing allele according to established expression levels-resulting in HiHi, HiLo, & LoLo genotype groups for analysis. We evaluated effects of gender and the promoter genotype on induction of negative affect by intravenous infusion of L: -tryptophan (TRP). The protocol consisted of a day-1 sham saline infusion and a day-2 active TRP infusion. Models assessed 5-HTTLPR composite genotype and gender as predictors of change in ratings of negative emotion during TRP infusion. During sham infusion there were no significant changes from baseline in mood ratings. During TRP infusion all negative affect ratings increased significantly from baseline (P's <.02). The genotype x gender interaction was a significant predictor of depression-dejection (P =.013), and trended towards predicting anger-hostility (P =.084). Males in the HiHi group had greater increases in negative affect during infusion, compared to all groups except LoLo females, who also showed increased negative affect.
This paper investigates transforms of split dependency grammars into unlexicalised context-free grammars annotated with hidden symbols. Our best unlexicalised grammar achieves an accuracy of 88% on the Penn Treebank data set, that represents a 50% reduction in error over previously published results on unlexicalised dependency parsing.
Modern statistical parsers are trained on large annotated corpora (treebanks). These treebanks usually consist of sentences addressing different subdomains (e.g. sports, politics, music), which implies that the statistics gathered by current statistical parsers are mixtures of subdomains of language use. In this paper we present a method that exploits raw subdomain corpora gathered from the web to introduce subdomain sensitivity into a given parser. We employ statistical techniques for creating an ensemble of domain sensitive parsers, and explore methods for amalgamating their predictions. Our experiments show that introducing domain sensitivity by exploiting raw corpora can improve over a tough, state-of-the-art baseline. 1.
This study examined the effects of appraisal of sexual stimuli on sexual arousal in women with superficial dyspareunia (n = 50) and sexually functional women (n = 25). To elicit different appraisals of an erotic film fragment, participants received an instruction prior to viewing it, with a focus on genital pain or on sexual enjoyment. A neutral instruction served as a control condition. Assignment to instruction condition was randomized. Genital arousal (vaginal pulse amplitude) and self-report ratings of affect and genital sensations were obtained in response to the erotic stimulus. As predicted, appraisal of the erotic stimulus affected genital responding, albeit marginally significant. Follow-up tests indicated that women who received the genital pain instruction responded with marginally significant lower genital arousal levels than women who received the sexual enjoyment instruction (d = 0.67). A significant instruction effect for negative affect was found, signifying that negative affect ratings were highest after the genital pain instruction and lowest after the sexual enjoyment instruction (d = 0.80). A marginally significant group by instruction interaction effect was observed for positive affect, indicating that women with dyspareunia reported significantly less positive affect than controls after the sexual enjoyment instruction (d = 1.48). Whereas women with dyspareunia reported overall marginally significant more negative affect than controls (d = 0.48), there were no differences in genital responsiveness between groups. These results provided preliminary evidence for the modulatory effects of appraisal of sexual stimuli on subsequent genital responding and affect in women with and without sexual complaints.
The cycle of lexicographic and linguistic work involved in compiling a computational phraseological database is divided into three phases and described in relation to the specific challenges multi-word expressions (MWEs) pose for a lexical database. Data collection is a process that is far from complete for the MWEs found in English, with the variability of some phrases making identification of all occurrences in large corpora a major challenge. Formalization of the form and variability ofMWEs is an interrelated process which can improve tools for data collection and other applications. Increased use of the phraseological lexical database in NLP applications can ultimately lead to further insights into the nature of MWEs and to improvements in the database. Due to the volume of lexicographic data on MWEs that still needs to be collected, analysed and formalized, and the cyclical nature of the work, the resulting lexical database should be reusable in as many applications as possible. WordManager-PhraseManager, the lexical resource described in the second part of the chapter, can capture the variability ofMWEs in a way that allows for maximum reusability of lexical data.
This article lays the empirical and methodological basis for the development of a lexical database that analyses the derivative morphology of Old English. After revising the state of the art; the working hypotheses are established and the descriptive principles for the analysis of tranparent as well as opaque derivation are established. Finally; a step is taken in the explanatory direction by defining the parameters of the analysis of the bases and adjunts of derivation that are relevant for explanation.
We present an approach to creating a treebank of sentences using multiple notations or linguistic theories simultaneously. We illustrate the method by annotating sentences from the Penn Treebank II in three different theories in parallel: the original PTB notation, a Functional Dependency Grammar notation, and a Government and Binding style notation. Sentences annotated with all of these theories are represented in XML as a directed acyclic graph where nodes and edges may carry extra information depending on the theory encoded. 1.
Both trait anger-in (managing anger through suppression) and anger-out (managing anger through direct expression) are related to pain responsiveness, but only anger-out effects involve opioid mechanisms. Preliminary work suggested that the effects of anger-out on postoperative analgesic requirements were moderated by the A118G single nucleotide polymorphism of the mu opioid receptor gene. This study further explored these potential genotypexphenotype interactions as they impact acute pain sensitivity. Genetic samples and measures of anger-in and anger-out were obtained in 87 subjects (from three studies) who participated in controlled laboratory acute pain tasks (ischemic, finger pressure, thermal). McGill Pain Questionnaire (MPQ) Sensory and Affective ratings for each pain task were standardized within studies, aggregated across pain tasks, and combined for analyses. Significant anger-outxA118G interactions were observed (p's<.05). Simple effects tests for both pain measures revealed that whereas anger-out was nonsignificantly hyperalgesic in subjects homozygous for the wild-type allele, anger-out was significantly hypoalgesic in those with the variant G allele (p's<.05). For the MPQ-Affective measure, this interaction arose both from low pain sensitivity in high anger-out subjects with the G allele and heightened pain sensitivity in low anger-out subjects with the G allele relative to responses in homozygous wild-type subjects. No genetic moderation was observed for anger-in, although significant main effects on MPQ-Affective ratings were noted (p<.005). Anger-in main effects were due to overlap with negative affect, but anger-outxA118G interactions were not, suggesting unique effects of expressive anger regulation. Results support opioid-related genotypexphenotype interactions involving trait anger-out.
In contrast to previous stress research, studies concerning phobic disorders have never systematically investigated individual response differences between phobic participants integrating numerous different response measures. The aim of this article is to clarify the existence of significant individual response differences in psychophysiological responses (e.g., heart rate, skin conductance responses (SCR), corrugator, cortisol), subjective ratings (e.g., valence, arousal), and avoidance behavior in 46 spider phobic and 44 non-phobic women when exposed to 20 phobic and 20 neutral pictures. Previous studies that did not attend to individual response differences showed that, during phobic stimulation, phobic individuals have increased psychophysiological responses (heart rate, SCR, and corrugator responses), more negative valence rating, and more subjective arousal than non-phobic individuals. These results were confirmed by our data. With regard to individual response uniqueness, 1/3-2/3 of spider-phobic women with low responsiveness in heart rate, cortisol, and avoidance behavior were indistinguishable from non-phobic women during phobic stimulation. With SCR, corrugator EMG, and subjective ratings, no individual response uniqueness was found. Based on the findings, exposure therapy might be improved by tailoring interventions to individuals with a therapeutic focus on those psychophysiological measures that show the highest individual responsivity.
In this paper we describe some technical and theoretical aspects related to a manually aligned bilingual treebank Italian (ITA) – Italian Sign Language (LIS) provided with both constituency and dependency annotation (Siena University Treebank, SUT). We briefly discuss the linguistic rationale behind the feature set and the dependency/constituency structure we adopted. Moreover we discuss the tool we used to annotate, semi-automatically, the treebank that, in the end, will be evaluated qualitatively with respect to a specific Transfer-Based Machine Translation (TB-MT) task.
Hungarian Academy of ScienceEötvös Loránd UniversityThis paper examines the Afro-Asiatic etymologies of Chadic lexical roots discussed by Olga V. Stolbova in her Chadic Lexical Database, Issue I (2005). The analysis is arranged according to the following sections: (1) Common Chadic reconstructions, (2) Isolated Chadic roots that nevertheless have Afro-Asiatic cognates. The paper represents the third part of my longer series of papers on addenda et corrigenda to Chadic lexical roots.