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16504 papers
The paper introduces three chunk parsing tasks carried in current CIPS parsing evaluation workshop(CIPS-ParsEval-2009),which is organized by Tsinghua University and Northeastern University.They are base chunk parsing,functional chunk parsing and event description clause recognition tasks.The designing motivation and the classification standards of these three chunks are discussed in the paper.Based on the detailed syntactic annotations in Tsinghua Chinese Treebank(TCT),three benchmark chunk banks automatically extracted from TCT are built.The evaluation results of top-5 participating systems are also given.The data analysis from their statistics and the comparison with current chunk schemes show some characteristics of these three chunk parsing tasks.
Among the benefits of a flexible and modular lexical database are: the facility of building new modules from existing ones, the reuse of lexicographic data to both enhance the user experience and achieve NLP aims, the time saved in accomplishing these objectives, and the economy that comes from minimizing redundancy (van der Eijk, Bloksma, and van der Kraan 1992). LUPo, or the Portuguese Unisyn Lexicon, is one of the first speech-dedicated applications to take full advantage of a collection of lexical resources as the basis for a text-to-speech system. Consisting of a pronunciation lexicon and rule system for generating accent-specific phonetic transcriptions for Portuguese, LUPo circumvents the cost of producing high-quality phonetic transcriptions by hand, while attracting a wider pan Lusophone audience to the lexical database in which it resides, and providing the research community with a vast resource of Portuguese accent data for evaluating speech applications and testing theories.
We investigate Arabic Context Free Grammar parsing with dependency annotation comparing lexicalised and unlexicalised parsers. We study how morphosyntactic as well as function tag information percolation in the form of grammar transforms (Johnson, 1998, Kulick et al., 2006) affects the performance of a parser and helps dependency assignment. We focus on the three most frequent functional\ntags in the Arabic Penn Treebank: subjects, direct objects and predicates. We merge these functional tags with their phrasal categories and (where appropriate) percolate case information to the non-terminal (POS) category to train the parsers. We then automatically enrich the output of these parsers with full dependency information in order to annotate trees with Lexical Functional Grammar (LFG)\nf-structure equations with produce f-structures, i.e. attribute-value matrices approximating to basic predicate-argument-adjunct structure representations. We present a series of experiments evaluating how well lexicalized, history-based, generative (Bikel) as well as latent\nvariable PCFG (Berkeley) parsers cope with the enriched Arabic data. We measure quality and coverage of both the output trees and the generated LFG f-structures. We show that joint functional and morphological information percolation improves both the recovery of trees as well as dependency results in the form of LFG f-structures.
Real world audio clips contain numerous acoustic sources. The rich acoustic information they carry cannot be fully described with single or even multiple terms about the acoustic sources alone. For instance, the label birds assigned to a birds singing clip that includes sounds of trees and a small river does not properly capture the experience it creates in the person listening to it. In this paper we introduce a novel scheme where the subjective experience of listening to sound clips containing mixture of sources is captured using affective measures. Furthermore, in contrast to the conventional approach of simple label-based methods, the affective ratings are then used to evaluate the performance of an example-based audio retrieval system. We argue that audio retrieval systems can benefit from using affective measures which are well established in experimental psychology, especially when dealing with real world audio clips. We present experimental results of our pilot study to support this motivation where the latent indexing framework has been employed for example-based retrieval on a collection of clips from the BBC sound effects library. The result of our study indicates that using the scheme of affective measures for representation and evaluation is indeed a promising direction to explore.
BACKGROUND: While research indicates cognitive biases in individuals vulnerable to bipolar symptoms, the specificity of these biases to the self and others, and to low or high activation states, is underexplored. METHOD: These biases were investigated using individuals with high (n = 24) and low levels (n = 24) of hypomanic personality (HPS) during word rating and free recall of a list of trait words after a positive versus neutral mood induction. RESULTS: The mood induction was not successful. Also, in contrast to the predicted self-serving bias, there was a self-denigratory bias in self-ratings relative to ratings of another person. In post hoc analyses, the study succeeded in producing a rating task of trait words that differentiated between high and low hypomania-prone individuals, as the high HPS group made higher ratings of high activation trait words (e.g. dynamic) to describe positive and neutral attributes regardless of whether it referred to themselves or another person. The high HPS group also showed a negative recall bias, but it was not specific to the self, questioning assumptions made about negative biases in existing research. Furthermore, a strong relationship emerged between greater use of imagery at encoding and greater recall of self-referent, positive, high activation words, suggesting a role for the intensity of images associated with the amplification of emotions in people with bipolar disorder (Holmes et al., 2008). CONCLUSIONS: It seems important to consider various multiple factors in memory bias research in people vulnerable to bipolar disorder, including self versus other encoding, high versus low activated states and the role of mental imagery. Further research is needed to spell out their interactive contribution.
Syntactic consistency is the preference to reuse a syntactic construction shortly after its appearance in a discourse. We present an analysis of the WSJ portion of the Penn Tree-bank, and show that syntactic consistency is pervasive across productions with various left-hand side nonterminals. Then, we implement a reranking constituent parser that makes use of extra-sentential context in its feature set. Using a linear-chain conditional random field, we improve parsing accuracy over the generative baseline parser on the Penn Treebank WSJ corpus, rivalling a similar model that does not make use of context. We show that the context-aware and the context-ignorant rerankers perform well on different subsets of the evaluation data, suggesting a combined approach would provide further improvement. We also compare parses made by models, and suggest that context can be useful for parsing by capturing structural dependencies between sentences as opposed to lexically governed dependencies.
Proceedings of the Ninth International Workshop \non Treebanks and Linguistic Theories. \nEditors: Markus Dickinson, Kaili Müürisep and Marco Passarotti. \nNEALT Proceedings Series, Vol. 9 (2010), 163-174. \n© 2010 The editors and contributors. \nPublished by \nNorthern European Association for Language \nTechnology (NEALT) \nhttp://omilia.uio.no/nealt. \nElectronically published at \nTartu University Library (Estonia) \nhttp://hdl.handle.net/10062/15891.
DeSR is a statistical transition-based dependency parser which learns from annotated corpora which actions to perform for building parse trees while scanning a sentence. We describe the experiments performed for the ICON 2010 Tools Contest on Indian Dependency Parsing. DesR was configured to exploit specific features from the Indian treebanks. The submitted run used a stacked combination of four configurations of the DeSR parser and achieved the best unlabeled accuracy scores in all languages. The contribution to the result of various choices is analyzed.
This paper presents a method for the automatic detection and correction of malapropism errors found in documents using the WordNet lexical database, a search engine (Google) and a paronyms dictionary. The malapropisms detection is based on the evaluation of the cohesion of the local context using the search engine, while the correction is done using the whole text cohesion evaluated in terms of lexical chains built using the linguistic ontology. The correction candidates, which are taken from the paronyms dictionary, are evaluated versus the local and the whole text cohesion in order to find the best candidate that is chosen for replacement. The testing methods of the application are presented, along with the obtained results.
We propose an effective approach to automatically identify predicate heads in Chinese sentences based on statistical pre-processing and rule-based post-processing. In the preprocessing stage, the maximal noun phrases in a sentence are recognized and replaced by “NP ” labels to simplify the sentence structure. Then a CRF model is trained to recognize the predicate heads of this simplified sentence. In the post-processing stage, a rule base is built according to the grammatical features of predicate heads. It is then utilized to correct the preliminary recognition results. Experimental results show that our approach is feasible and effective, and its accuracy achieves 89.14 % on Tsinghua Chinese Treebank. 1
In this paper, we discuss our analysis and resulting new annotations of Penn Discourse Treebank (PDTB) data tagged as Concession. Concession arises whenever one of the two arguments creates an expectation, and the other ones denies it. In Natural Languages, typical discourse connectives conveying Concession are ‘but’, ‘although’, ‘nevertheless’, etc. Extending previous theoretical accounts, our corpus analysis reveals that concessive interpretations are due to different sources of expectation, each giving rise to critical inferences about the relationship of the involved eventualities. We identify four different sources of expectation: Causality, Implication, Correlation, and Implicature. The reliability of these categories is supported by a high inter-annotator agreement score, computed over a sample of one thousand tokens of explicit connectives annotated as Concession in PDTB. Following earlier work of (Hobbs, 1998) and (Davidson, 1967) notion of reification, we extend the logical account of Concession originally proposed in (Robaldo et al., 2008) to provide refined formal descriptions for the first three mentioned sources of expectations in Concessive relations. 1.
Towards human consistent data driven decision support systems using verbalization of data mining results via linguistic data summaries We present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the essence of data that may be relevant for a business activity. The use of linguistic summaries provides tools for the verbalization of data analysis (mining) results which, in addition to the more commonly used visualization e.g. via a GUI, graphical user interface, can contribute to an increased human consistency and ease of use. The results (knowledge) derived are in a simple, easily comprehensible linguistic form which can be effectively and efficiently employed for supporting decision makers via the data driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which was first initiated by the authors. First, following Kacprzyk and Zadrożny [1] comments are given on an extremely relevant aspect of scalability of linguistic summarization of data, using their new concept of a conceptual scalability that is crucial for large applications. Second, following Kacprzyk and Zadrożny [2] it is further considered how linguistic data summarization is closely related to some types of solutions used in natural language generation (NLG), which can make it possible to use more and more effective and efficient tools and techniques developed in this another rapidly developing area. An application of a computer retailer is outlined.
In this paper authors will show how verb valency data, added to the Croatian dictionary in NooJ, enhances recognition of VP as well as NP and PP parts of a sentence. At the Department of Information Sciences two parallel PhD Theses were being developed. One is construction of a chunker for Croatian using NooJ and the other one is construction of Croatian verb valency lexicon (CRVLLEX). Here we combined the two projects by adding the data from CRVLLEX to the existing NooJ dictionary hoping thus to obtain better, improved Croatian chunker results. Our dictionary has over 36 000 entries of which 1 884 are verbs. Each verb is only marked by its category and the FLX. Additional data is being added from the CRVLLEX. Theoretic motivation behind the construction of CRVLLEX is Praha’s Dependency Treebank (PDT) but also good Czech verb valency dictionaries (VALLEX and Verbalex). So far, CRVLLEX has 1 739 verbs with 5 118 valency frames (approx. 3 frames per verb) and 173 syntactic-semantic classes. Each word entry in CRVLLEX contains headword lemma, reflexivity example (depending whether the verb is reflexive or not) and frame entry which is the part that describes the valency frame for each verb. Every verb also has the following attributes: aspect, frequency and form, which we hope will be of great importance in disambiguating parts of a sentence surrounding the verb.
This study utilized a unique contact lens method to examine the influence of right hemisphere processing on affective judgments and pain perception. Under conditions of unilateral visual stimulation, participants completed affective ratings of films and underwent a cold pressor pain task. The goal was to examine differences in affective judgments of films projected to one or the other hemisphere and to examine the influence of this unilateral visual stimulation on pain sensitivity. The results failed to replicate a previous finding of differential affective judgments under conditions of right and left visual stimulation. Nonetheless, in female subjects, unilateral visual stimulation was significantly associated with pain lateralization. This finding is discussed in terms of attentional processes in pain perception and limitations of the current lens design.
Despite the prevalence of infidelity, there is relatively little research regarding the long-term effects on the children. Combining the views of transgenerational theory with the existing literature on infidelity as a family stressor and infidelity as a trauma, this project examines the potential lasting effects of parental infidelity on the adult child. Study participants included a small sample of adults over the age of 18 who were aware of parental infidelity in their family of origin. Through a series of regression analyses using a moderator model, the researchers found that higher negative self schemata and affect ratings related to the perception of the infidelity were associated with more conservative attitudes toward sex. Suggestions for future utilization of the proposed model and the clinical implications of the findings are also discussed.
The dissertation presents one of the possible models of processmg extended textual coreference and bridging anaphora in a large textual corpora, which we then use for annotation of certain relations in texts of the Prague Oependency Treebank (POT). Based, on the one hand, on the literature concerning the theory of reference, discource and some findings of theoretical linguistics, and, on the other hand, using the existing methodology of annotations, we created a detailed classification of textual coreferential relations and types of bridging anaphora. Within textual coreference, we distinguish between two types of textual coreferential relations - coreferential relations between noun phrases with specific reference and coreferential relation between noun phrases with non-specific, primarily generic, reference. We determined six types of relations for bridging anaphora: relation PART- between part and whole; relation SUBSET - between a set and a subset or element of a set; FUNCT - between an object and a unique function on that entity; CONTRAST- between semantíc and contextual opposites; relation ANAF of anaphorical referencing between noncoreferencial objects; REST- for other examples of bridging anaphora. One of the goals of the research is to create a system of theoretical principals that would be used...
Exclusive experience with standardized languages produces an expectation that speech community members will assess competing variants by their supposed correctness. This does not happen in the persistently divergent but socially neutral variant use of Embo Gaelic speakers, including close kin and age mates. Communities elsewhere show both variation akin to Embo's personal‐pattern variation and similar social‐organization and social‐setting features: small population size, isolation, use of a minority language unrelated/distantly related to the dominant language, weak/absent extra‐community linguistic norms, social homogeneity with high interaction density and multiplex social roles, absence of linguistic accommodation. The ideologies of linguists from dominant‐language societies hamper recognition of different linguistic ideologies among other peoples. The importance of personal‐pattern variation to individual voice in homogeneous communities is discussed and exemplified. Ongoing transmission of individual variant‐use patterns is seen to have been in keeping with high‐variation language input to children and with diffuse child‐care patterns and peer‐group structure.
The greatest American writer Eugene O'Neill (1888- 1953) achieved a recognizable place among the English and American dramatists through the stylistic features of his dramatic language. This study investigates O'Neill's way of handling dramatic language, in Hairy Ape,( the use of grammar from the settled norms in play writing). It endeavors to show how O'Neill manipulates his character's dialogue and the effects of this manipulation.The problem is related to what extent O'Neill's use of language deviates from the linguistic norm, and the levels of linguistic deviation in his style. The study aims to analyze the types of grammatical deviation in O'Neill's 'Hairy Ape'. Moreover, it attempts to justify the reasons behind these deviations (and to support some critical points of view concerning O'Neill's and style in using grammatical deviations).. Deviation as a linguistic phenomenon has an important effect on the readers (and hearers ), if a part of a poem is deviant it becomes especially, noticeable, or perceptually prominent ( Short, 1969: 11 ). Out of the stylistic analysis,it has been found out that the writer uses a language deviated from the literary convention or everyday speech(norm). He uses different types of linguistic deviations to achieve his purposes.
Review by Shannon Sauro, University of Texas at San Antonio Naomi Baron’s (2008) Always On: Language in an Online and Mobile World, provides an overview of trends in digital communication and the impact these trends and practices have for personal interconnectivity, literacy, attitudes towards privacy and ownership, and the ongoing negotiation of linguistic norms. Formatted as a popular book (i.e., each chapter includes social commentary in the form of comics and cartoons, and in-text citation is replaced with chapter notes at the end of the book), Always On has a target audience that includes the non-specialist interested in the ongoing debate regarding the impact of technology on language and society (see, for example, Crystal, 2008) as well as scholars and students involved in research on computer-mediated communication.
Change of first language (L1) status from the most stable language to a less accessible language over the life-span of a bilingual individual is termed ‘language attrition’. Such a shift in ease of L1 access has been reported to affect the lexicon (Pelc, 2001) more than other aspects of language. However, whether L1 attrition is affected by reduced L1-strength or increased second language (L2) interference is unresolved. This study was designed to understand the relative contributions of L1-strength (Ebbinghaus, 1885; Paradis, 2001, 2007) and L2-interference (Loftus & Loftus, 1980; Gürel, 2004) towards L1 attrition in L2-dominant bilingual individuals, and how attrition is affected by language use and proficiency. We used a cross-modal (picture-auditory word) and cross-linguistic (Bengali-English) lexical priming paradigm in order to test the nature of L1-L2 interaction in 27 Bengali-English-speaking individuals. Participants were divided into two groups (L1-dominant and L2-dominant) varying in relative L1-L2-proficiency. Familiarity ratings for English words and their translation equivalents permitted generating four word-pair categories: HighEnglish-HighBengali, LowEnglish-LowBengali, HighEnglish-LowBengali and LowEnglish-HighBengali. Reaction time (RT) and Event related potentials (ERPs) were recorded to a syllable-judgment task for the auditory word. Participants also rated themselves on language and reported language use. We hypothesized that if reduced L1-strength affected L1 attrition, Bengali words from all four word-pair categories would elicit longer RTs and larger negative ERPs than English words. In contrast, if L2-interference affected L1 attrition, all Bengali words except ones from the LowEnglish-HighBengali category would elicit longer RTs and larger negative ERPs compared to their English translations. Results showed participants’ L1-use and L2 self-ratings predicted performance in L1. Behavioral data showed longer RTs for Bengali than English in the HighBengali-HighEnglish category and longest RTs for English in the LowEnglish-HighBengali category. ERP data showed greater negativities to English and Bengali words from the category with low familiarity English ratings regardless of their Bengali ratings. Different results from the two measures of the lexical task suggest that each task reflects a different point in the process of lexical access. Overall, findings suggested that L2-interference into L1 plays a larger role in L1 attrition in L2-dominant individuals.
MICA is a fast and accurate dependency parser for English that uses an automatically LTAG derived from Penn Treebank (PTB) using the Chen's approach. However, there is no semantic representation related to its grammar. On the other hand, XTAG grammar is a hand crafted LTAG that its elementary trees were enriched with the semantic representation by experts. The linguistic knowledge embedded in the XTAG grammar caused it to being used in wide variety of natural language applications. However, the current XTAG parser is not as fast and accurate as well as the MICA parser. Generating an XTAG derivation tree from a MICA dependency structure could make a bridge between these two notions and gets the benefits of both models. Also, by having this conversion, the applications that use the XTAG parser, may get the helps from MICA parser too. In addition, it can enrich the MICA's grammar by semantic representation of XTAG grammar. In this paper, an unsupervised sequence tagger that maps any sequence of MICA elementary trees onto an XTAG elementary trees sequence is presented. The proposed sequence tagger is based on a Hidden Markov Model (HMM) proceeded by an EM-based algorithm for setting its initial parameters values. The trained model is tested on a part of PTB and about 82% accuracy for the detected sequences is achieved.
We investigate in this paper the adequate unit of analysis for Arabic Mention Detection. We experiment different segmentation schemes with various feature-sets. Results show that when limited resources are available, models built on morphologically segmented data outperform other models by up to 4F points. On the other hand, when more resources extracted from morphologically segmented data become available, models built with Arabic TreeBank style segmentation yield to better results. We also show additional improvement by combining different segmentation schemes. 1
This paper proposes how to convert projective dependency structures into flat phrase structures with language-independent syntactic categories, and use a head finder algorithm to convert these phrase structures back into dependency structures. The head finder algorithm is implemented by a maximum entropy approach with constraint information. The converted phrase structures can be parsed using a hierarchical coarse-to-fine method with latent variables. Experimental results show that the approach finds 98.8% heads of all phrases, and our algorithm achieves state-of-the-art dependency parsing performance in English Treebank.
Lexicon-Grammar tables are a very rich syntactic lexicon for the French language. This linguistic database is nevertheless not directly suitable for use by computer programs, as it is incomplete and lacks consistency. Tables are defined on the basis of features which are not explicitly recorded in the lexicon. These features are only described in literature. Our aim is to define for each tables these essential properties to make them usable in various Natural Language Processing (NLP) applications, such as parsing.
Lexicon-Grammar tables are a very rich syntactic lexicon for the French language. This linguistic database is nevertheless not directly suitable for use by computer programs, as it is incomplete and lacks consistency. Tables are defined on the basis of features which are not explicitly recorded in the lexicon. These features are only described in literature. Our aim is to define for each tables these essential properties to make them usable in various Natural Language Processing (NLP) applications, such as parsing.
This paper proposes an novel approach to annotate function tags for unparsed text. What distinguishes our work from other attempts in such task is that we assign function tags directly basing on lexical information other than on parsed trees. In order to demonstrate the effectiveness and versatility of our method, we investigate two statistical models for automatic annotation, one is log-linear maximum entropy model and the other is margin maximum based support vector machine model, which achieve the best F-score of 82.8 and 86.4 respectively when tested on the text from Penn Chinese Treebank. We also quantity the effect of POS tagger accuracy on system performance. Our results indicate that the function tag types could be determined via flexible and powerful feature representations from words, POS tags and word position indicators, and that, similarly to syntactic parsing, the main difficulty lies in complex constituents with long-distance dependency.
From the perspective of translation, Lestrygonians is a chapter that goes in the face of linguistic norm, subverting expectations of standard language use. The chapter consistently shows meaning to be unstable, self-generating along lines of flight, mushrooming around nodes of (semantic) tension. The cohesion of the text, as shown in the sandwich’ passage, depends on a series of such nodes, of linguistic occasions, associations and interfaces; Bloom’s associations and bricolage (or, to use Jean- Michel Rabaté’s pun, brick-holing)1 of words which direct and channel the text’s movements are called forth by the shape of phrases, homonymy and polysemy. Such instability of meaning and of the directions of the production of meaning certainly musters and breeds translation problems: the translator would have to aim at finding/ creating analogous interfaces in the target language (TL) that could account for, and function as points of departure for Bloom’s strings of associations, for the text’s nodes of meaning and tension.
We present a new reference Grammar of French (La Grande Grammaire du français), which is a collective project (gathering around fifty contributors), producing a book (about 2200 pages, to be published en 2011) and associated databases. Like the recent reference grammars of the other Romance Languages, it takes into account the important results of the linguistic research of the past thrity years, while aiming at a non specialist audience and avoiding formalization. We differ from existing French grammar by being focused on contemporary French from a purely descriptive point of view, and by taking spoken data into account. We include a description of all the syntactic phenomena, as well as lexical, semantic, pragmatic and prosodic insights, specially as they interact with syntax. The analysis concerns the data from contemporary written French, but also includes data from spoken corpora and regional or non standard French (when accessible). Throughout the grammar, a simple phrase structure grammar is used, in order to maintain a common representation. The analyses are modular with a strict division of labor between morphology, syntax and semantics. From the syntactic point of view, POS are also distinguished from grammatical relations (or functions). The databases include a terminological glossary, different lexical databases for certain POS, certain valence frames and certain semantic classes, and a bibliographical database. 1. Presentation of the project Sizable comprehensive grammars, written by linguists but aiming at a larger audience, have been published for several European languages: for Italian, the Grande
Linguistic variants are elements that are considered identically in terms of functionality, though they differ formally. The present article discusses variant forms of nouns. The study refers both to variants in the strict sense, i.e. identical in terms of function, and oscillating variants, i.e. those that differ in one quality, i.e. chronology, frequency, social range, stylistic character or the degree of expressiveness or emotiveness. The examples have been excerpted from Nowy słownik poprawnej polszczyzny PWN [The PWN New Dictionary of Correct Polish Usage]. The collected material has been classified into several groups depending on the relations between variants defined by means of qualifiers and abbreviations. Formal and linguistic expressions of noun variantivity are also presented. The examples under scrutiny indicate that the linguistic norm (standard) accepts far more nominal variant forms than the linguistic custom presents as it has sanctioned only a certain part of the analysed examples. A detailed and thorough study on the functioning of nominal variants in the linguistic custom is, however, difficult to carry out.
A layer-based projective dependency parsing approach is presented.This novel approach works layer by layer in a bottom-up manner,in which the depth of token dependency is allowed no more than one.Inside the layer the dependency graphs are searched exhaustively while between the layers the parser state transfers deterministically.Taking the dependency layer as the parsing unit,the proposed parser has a lower computational complexity than graph-based models which search for a whole dependency graph,alleviating the error propagation in transition-based models to some extent.Furthermore,our parser adopts the sequence labeling models to find the optimal sub-graph of the layer,which demonstrates the sequence labeling techniques qualified for hierarchical structure analysis tasks.Experimental results indicate that the proposed approach offers desirable accuracies and especially a very fast parsing speed,with 2500 words per second for Penn Treebank.
Whereas dictionary design has traditionally been guided by the results of dictionary use research, recent approaches in lexicographic research are strictly user-centred. We support the idea of integrating empirical cognitive evidence into this type of research, thus fruitfully exploiting it for both, the selection (and subsequently presentation) of lexical data and the acquisition of such data from corpora. Focusing on the extraction of semantic relations to be illustrated in electronic learners ’ dictionaries, we analyse the results of two behavioural experiments on the production as well as the perception of semantic relations. The main goal of the experiments was to determine which relations are cognitively salient in speakers ’ minds. With the objective of developing a method to automatically extract cognitively salient semantic relations from corpora, we describe and discuss findings of the first analyses conducted on composite part relations. In future this might serve as a basis for the elaboration of new strategies aimed at enriching lexical databases and dictionaries.
Do you ever complete, select, write, or administer rating scales to provide data for decision making? NO? Then you must be working in a storm drain. Most faculty developers I know have a wide variety of rating scales that fly across their desk tops as their incremental program activities unfold during the academic year. The primary issue for this column is: What is the quality of those ratings used for decisions about people and programs? When students, faculty, and administrators rate a program or someone's performance, we assume that they will read each item carefully and make their honest assessment with scrupulous impartiality (LOL). Are we dreaming in 3D IMAX like Avatar? The problem is that human tendencies may contaminate their responses, rendering them less than honest and impartial. In fact, these tendencies may be driven by demonic forces, such as those seen on Fringe or The Vampire Diaries or appearing in Stephen King's books. However, they may be conscious and intentional or unconscious. These tendencies are known as response sets or biases. More than 10 types of bias can affect ratings, such as halo effect; end-aversion bias; extreme-response bias; acquiescence bias; and gender, racial/ ethnic, and sexual orientation bias. There are four that particularly afflict faculty or administrator ratings: leniency-stringency bias, incompetence bias, buddy bias, and back-scratching bias. Your awareness of these biases and the techniques to minimize or eliminate them can produce more accurate ratings and foster more perceptive decisions than those currently being made. These biases are briefly described next along with suggestions for minimizing their effects. For a more detailed, rollicking treatment of the topic with research citations, see Berk (2006), Nunnally and Bernstein (1994), and Streiner and Norman (1995). 1. Halo Effect This effect is the extent to which a rater's overall impression of a person will affect his or her rating on each item. For example, if the global impression is positive and a student really likes her instructor, she may simply mark Strongly Agree to all positive statements. However, despite the positive image of a halo on an angel (Remember: The TV series Touched by a Halo?), this effect can also be negative, such as when a student hates the course. Possible solutions: Since this is an individual bias, the larger the group of raters, the greater the chance that positive and negative halo effects will cancel each other out. Unfortunately, there is no simple solution to control or minimize halo effect. 2. End-Aversion/Central Tendency Bias This is the tendency to ignore the extreme response options or anchors on the scale because they may be viewed as too strong. When the extremes are not selected, the ratings may be squished into the middle of the scale, which restricts the range of responses. Possible solutions: This bias should not be a problem on most rating scales in the agree-disagree format. However, scales consisting of several evaluation anchors, such as excellent-poor, or frequency anchors with absolutes, such as always-never, can produce this type of bias. Either soften the extreme anchors with Almost Always and Almost Never, or extend the number of anchors with the expectation that the extremes will rarely be chosen. 3. Extreme-Response Bias This is the opposite of end-aversion bias. In this case, the respondents may mark the extreme anchors rather than those in between. This bias is difficult to detect because the reason for the choice of the extremes may also be due to their honest ratings or the halo effect. Possible solution: This type of bias may occur less often than the other sources of bias. However, there is no direct solution. 4. Acquiescence/Affirmation/ Agreement/Yea-Saying Bias This is the tendency to agree or give positive responses to statements irrespective of their content. …
1 Many researchers have explored the topic with the intent of identifying the logic of the variation between CC and non-CC. In this paper we want to address a specific problem pointed out in the literature about CC in Spanish: its incidence is far less frequent in written texts. This can be interpreted as a problem in face of the diachronic evolution of the phenomenon, which showed higher frequency in medieval times. Therefore, the tendency for grammatical innovations (non-CC) to be more common in speech seems to be contradicted. I want to shed light on this problem by assigning the difference between registers to the dependence of the phenomenon to Information Structure. In order to do so, I demonstrate not only that register is a relevant variation factor in European Portuguese (EP), but also that it is connected to internal factors which are relevant to understand variation. The paper presents the results from a EP corpus made up of about 1,000 data from different registers and sources: we have collected sentences from interviews given to linguistic databases and newspapers through the Corpus do Portugues (Davies & Ferreira 2006), and from contemporary Portuguese novels, all listed in the Appendix. The sentences include a finite verb followed by an infinitive, once CC is obligatory in EP in verb sequences involving a gerund or a participle. Before moving along, it is necessary to differentiate between two constructions that show CC: and union. 2 While restructuring is usually linked to governing verbs of the modal, aspectual and movement classes which usually display semantic bleaching - see (1) - in union the governing verb is causative or perceptive. A verb of the latter type selects a complement with a non-coreferent subject. This embedded subject occurs in accusative or dative form, and climbs obligatorily, alongside other clitics - (2)b. Once there is no variation with respect to CC in clause union, we will only deal with restructuring data, similarly to previous studies about variation in CC.
The past several years have witnessed rapid advances in syntax-based machine translation, which exploits natural language syntax to guide translation. Depending on the type of input, most of these efforts can be divided into two broad categories: (a) string-based systems whose input is a string, which is simultaneously parsed and translated by a synchronous grammar (Wu, 1997; Chiang, 2005; Galley et al., 2006), and (b) tree-based systems whose input is already a parse tree to be directly converted into a target tree or string (Lin, 2004; Ding and Palmer, 2005; Quirk et al., 2005; Liu et al., 2006; Huang et al., 2006). Compared with their string-based counterparts, tree-based systems offer many attractive features: they are much faster in decoding (linear time vs. cubic time), do not require sophisticated binarization (Zhang et al., 2006), and can use separate grammars for parsing and translation (e.g. a context-free grammar for the former and a tree substitution grammar for the latter). However, despite these advantages, most treebased systems suffer from a major drawback: they only use 1-best parse trees to direct translation, which potentially introduces translation mistakes due to parsing errors (Quirk and Corston-Oliver, 2006). This situation becomes worse for resourcepoor source languages without enough Treebank data to train a high-accuracy parser. This problem can be alleviated elegantly by using packed forests (Huang, 2008), which encodes exponentially many parse trees in a polynomial space. Forest-based systems (Mi et al., 2008; Mi and Huang, 2008) thus take a packed forest instead of a parse tree as an input. In addition, packed forests could also be used for translation rule extraction, which helps alleviate the propagation of parsing errors into rule set. Forest-based translation can be regarded as a compromise between the string-based and tree-based methods, while combining the advantages of both: decoding is still fast, yet does not commit to a single parse. Surprisingly, translating a forest of millions of trees is even faster than translating 30 individual trees, and offers significantly better translation quality. This approach has since become a popular topic.
Human communication takes place in both spoken and written modes, as in face-to-face conversations, books reading, television watching and Internet browsing. However, for people with language disabilities (e.g. aphasia), people with low literacy, and people with poor command of a language, receiving and expressing information via a language is difficult. Because of the inability to comprehend words and/or to find words that express intended concepts, people with language barriers may encounter great challenges performing everyday tasks such as ordering food and visiting a doctor. As an alternative to words, pictures and sounds have been designed, tested, and used to evoke concepts in computer-based interfaces, education, industry, and advertisement. However, icons created by artists, user-uploaded photos, auditory icons and earcons cannot always satisfy the need for communicating everyday concepts for people with language barriers. Furthermore, the iconic vocabularies in current communication support systems have ambiguous representations and difficult to use vocabulary organization. My thesis research addresses issues in the above paragraph and explores building multimedia support for information delivery. The work is unique in that it provides different channels (visual and auditory) to support nonverbal communication, and that it has a disambiguated sense-level network structure with semantic links between related concepts. The development of such a multimedia-enhanced lexical database is challenging, due to the lack of guidance in the creation and evaluation of multimodal representations. To construct the lexical database, I went through a cycle of design, construction, evaluation, and modification for each media modality-to-concept association. I have introduced novel representations that are under investigated (e.g. videos and environmental sounds). I have explored difference sources of multimedia data (designed by specialists, designed by general users, and web resources not tailored for communication purposes). I have experimented with new methodologies for generating and evaluating multimedia-concept associations. I have also come up with essential guidelines for better multimedia vocabulary design. A communication support system, the Online Multimedia Language Assistant (OMLA), which employs various multimedia forms, including web images, icons, animations, videos, and environmental sounds, was built on top of my research on multimedia representations with the goal of assisting comprehension of common concepts across language barriers. OMLA is implemented as a popup dictionary in the form of a web browser extension. Users can select an unfamiliar word on a webpage to view its associated visual/auditory representation in a popup box. The Language Assistant can enhance concept understanding as people browse information on the Internet, and support face-to-face communication when people want to illustrate a term via a picture, a video or a sound. Through a series of studies, I verified that web images are as effective as stylized icons in conveying nouns, that videos outperformed other stimuli in illustrating verbs, and that nonspeech sounds are better in distinguishing many concepts like thunder, alarms, and sneezing. The Multimedia Augmented Online Language Assistant was shown to enhance information comprehension, and I am exploring its application in real life scenarios such as medical care.
Building up messages as a cognitive activity within the linguistic multi-level system is the result of the interaction between the various components of this system. Yet, this interactive process occurring in the language user's mind while encoding can vary from person to person. Likewise, it also differs in different recipients while decoding. This cognitively carried out difference in encoding can result in either unintended messages, though emptied out in mature and well-formed language constructions, or ill-formed ones. The present study aims at identifying the most frequent syntactic errors at the sentential level; and how immature or vague conceptualization manifests itself in the grammar-meaning relationship as reflected in the subjects' errors. Data were collected from the writings and the performance tests of mainly two Arab groups of third and fourth-year English majors in the course of Sociolinguistics at the University of Nizwa in the Sultanate of Oman. Errors were identified, classified and interpreted in terms of the underlying cognitive processes they went through during production. Errors were related to time-tense vague mapping, finite-nonfinite confusion, sentence-clause uncertainty, incorrect embedding, voice-related inaccuracy and verbless clauses or sentences. ********** Errors in second language performance are easy to observe, and undoubtedly serve as good indicators of a learner's level of second-language knowledge. Thus, they are an integral component of language learning. The phenomenon of error has received the interest of researchers, though traditionally has been regarded as the linguistic phenomena deviant from the language rules and standard usages, reflecting learners' deficiency in language competence. Hence, many teachers simply correct individual errors as they occur, giving little concern to identifying patterns of errors or to uncovering causes other than learner ignorance. However, interpreting what the cause of these errors has been a major concern for linguists, as well as classroom practitioners. In this respect, Steinberg and Sciarini (2006), state that the systematicity of most errors is the result of the application of certain strategies when relevant second-language knowledge is not available or incomplete. Conscious resort to any of these strategies is definitely a cognitive exercise, the results of which are various deviations of the linguistic norms, sentence patterns and rules that put the language components together to produce linguistic moulds embodying composites of thoughts. Presently, therefore, with the development of linguistics, applied linguistics, psychology and other relevant subjects, attitudes toward errors changed greatly. Instead of being problems to be overcome, errors are viewed as an evidence of the learners' stages in their target language (TL) development. It is through analyzing learner errors that errors are elevated from the status of undesirability to that of a guide to the inner working of the language learning process, as (Ellis, 1985, cited by Nassaji & Fotos, 2004, at http://faculty.ksu.edu.sa/dinaalsibai/ReviewGrammar.PDF) puts it. The term grammar is used in this paper to include the two language levels of syntax and morphology since some errors in one level cannot be explained in isolation from the other. For example, the past tense of bring is brought, a case of inflection under morphology, whereas the interrogative form Did bring them? of Ali brought them is a syntactic issue. Memory and logic, which are cognitive skills, play a crucial role in language learning. As Steinberg and Sciarini (2006: 34-35) state it, that while learning to identify the words of the language, formulating rules for their use, and relating speech to the environment and mind, the child employs an exceptional memory capacity. In this respect, a massive number of particular words, phrases and sentences have to be remembered in connection with the context, whether physical or mental, in which they took place. …
Introduzione L’impiego di corpora elettronici nella ricerca linguistica si rivela partico larmente efficace quando ai dati raccolti ( raw data ) vengono aggiunte informazioni di carattere linguistico e funzionale che facilitano la loro in terpretazione da un punto di vista morfosintattico. Il risultato di tali pro cedure di analisi e rappresentato da Treebanks ovvero corpora annotati sintatticamente attraverso rappresentazioni ad albero. Solitamente distinta dalla procedura di mark-up , l’annotazione di un corpus realizzata con l’applicazione di sistemi computerizzati ( parsers ) che eseguono un’etichettatura delle parti del discorso ( POS tagging ) costituisce una procedura particolarmente efficace nel chiarire, ad esempio, casi di ambiguita grammaticale in cui un lessema, se privo di annotazione, puo essere interpretato sia come verbo (V) che come nome (N) (ad esempio work ). I parsers generalmente propongono descrizioni delle produzioni linguistiche di una comunita di parlanti basate su regole grammaticali estratte da un campione di dati e tale caratteristica talvolta non permette di eseguire l’analisi automatica anche di frasi non grammaticali . Si tratta, dunque, di sistemi di analisi basati su grammatiche di precisione che di stinguono principalmente cio che e grammaticale da cio che non lo e ba sandosi su un corpus necessariamente limitato di dati, in quanto la descri zione fa esclusivamente riferimento a campioni di frasi grammaticalmen te corrette di una lingua inseriti nel sistema. Tuttavia, la propensione dei parlanti a produrre costruzioni che presentano “deviazioni” dalla norma e il fatto che molti di essi usino una lingua straniera come strumento di co municazione comporta in se «that naturalistic ungrammatical sentences are of interest to linguists studying language production, language loss and language learning, and that the grammatical/ungrammatical distinc tion cannot therefore be completely dismissed» .
This study investigates how the duration of the stem vowel of regular and irregular English verbs is modulated by tense (present and past), regularity, lexical frequency, gang size of the vocalic alternation, imageability ratings, and vowel quality. The vocalic durations of 48 monosyllabic irregular verbs and 171 regular verbs were extracted from the Buckeye Corpus of spontaneous speech. A linear mixed effects regression model revealed that vowels of past tense forms tend to have longer durations than vowels of present tense forms, that vowels of words that are less imageable are realized with shorter durations, and that tense vowels are longer than lax vowels. Surprisingly, higher frequency irregular past tense forms were produced with longer vowels, contradicting Aylett and Turk [(2004); (2006)] and Bell et al. [(2003); (2009)]. Further, vowels were shorter for irregular verbs with larger vocalic alternation gangs, contradicting the predictions of Kuperman et al. [(2007)] but supporting hypotheses that units with a smaller information load have shorter durations. This pattern of results is interpreted as a consequence of the pressure for regularization during the production of irregular past tense forms.
Motion pictures are so typical experience goods that consumers tend to look for more credible information. Hence, movie audiences consider movie viewers` reviews more important than the information provided by the film distributor. Recently many portal sites allow consumers to post their reviews and opinions so that other people check the number of consumer reviews and scores before going to the theater. There are a few previous researches studying the electronic word of mouth(eWOM) effect in the movie industry. They found that the volume of eWOM influenced the revenue of the movie significantly but the valence of eWOM did not affect it much (Liu 2006). The goal of our research is also to investigate the eWOM effects in general. But our research is different from the previous studies in several aspects. First, we study the eWOM effect in Korean movie industry. In other words, we would like to check whether we can generalize the results of the previous research across countries. The similar econometric models are applied to Korean movie data that include 746,282 consumer reviews on 439 movies. Our results show that both the valence(RATING) and the volume(LNMSG) of the eWOM influence weekly movie revenues. This result is different from the previous research findings that the volume only influences the revenue. We conjectured that the difference of self construal between Asian and American culture may explain this difference (Kitayama 1991). Asians including Koreans have more interdependent self construal than American, so that they are easily affected by other people`s thought and suggestion. Hence, the valence of the eWOM affects Koreans` choice of the movie. Second, we find the critical defect of the previous eWOM models and, hence, attempt to correct it. The previous eWOM model assumes that the volume of eWOM (LNMSG) is an independent variable affecting the movie revenue (LNREV). However, the revenue can influence the volume of the eWOM. We think that treating the volume of eWOM as an independent variable a priori is too restrictive. In order to remedy this problem, we employed a simultaneous equation in which the movie revenue and the volume of the eWOM can affect each other. That is, our eWOM model assumes that the revenue (LNREV) and the volume of eWOM (LNMSG) have endogenous relationship where they influence each other. The results from this simultaneous equation model showed that the movie revenue and the eWOM volume interact each other. The movie revenue influences the eWOM volume for the entire 8 weeks. The reverse effect is more complex. Both the volume and the valence of eWOM affect the revenue in the first week, but only the volume affect the revenue for the rest of the weeks. In the first week, consumers may be curious about the movie and look for various kinds of information they can trust, so that they use the both the quantity and quality of consumer reviews. But from the second week, the quality of the eWOM only affects the movie revenue, implying that the review ratings are more important than the number of reviews. Third, our results show that the ratings by professional critics (CRATING) had negative effect to the weekly movie revenue (LNREV). Professional critics often give low ratings to the blockbuster movies that do not have much cinematic quality. Experienced audiences who watch the movie for fun do not trust the professionals` ratings and, hence, tend to go for the low-rated movies by them. In summary, applied to the Korean movie ratings data and employing a simultaneous model, our results are different from the previous eWOM studies: 1) Koreans (or Asians) care about the others` evaluation quality more than quantity, 2) The volume of eWOM is not the cause but the result of the revenue, 3) Professional reviews can give the negative effect to the movie revenue.
Based on the verdicts in A Dream of Red Mansions and their translations,this paper studies the co-existence of and transmission between binary elements in translation from the perspectives of media,physical existence,aesthetic techniques and function to probe into the artistic and scientific qualities of translation,with the combination of Chinese traditional literary theory and modern linguistic norm.The attention to the binary elements in translation can help avoid the intuitive perception and the rigid linguistic analysis in translation and guarantee both the flexibility of literary pattern and the scientific nature of modern linguistic norm in translation criticism.
This article describes psycholinguistic lexical databases available in various languages, including English, Spanish and Portuguese. These lexical databases are important for researchers in Psycholinguistics and other related areas, providing a pool of experimental materials and allowing for an efficient process of selection of these experimental materials. The process of gathering statistics is slow, resulting in a small pool of materials in the short-term. The need to find an alternative method to gather limited or yet unavailable statistics for a specific language led us to consider gathering statistics from other languages and to compute their triangulation. Our aim was to automatize the computation of statistics such as Familiarity, Imageability, Age of Acquisition and Written Word Frequency for that specific language. We will describe the process of preparing this data and triangulating and comparing statistics for some languages in an attempt of finding a relationship between them. The results were analysed considering correlations between each statistic in each pair of languages and by computing the mean of absolute differences between each language’s values.
Lexicography and language technology have traditionally been seenas two distinct disciplines. In addition to pointing at the commonneed to manage huge lemma lists in one way or another, the presentpaper argues for conducting lexicographical and language technologyprojects in an integrated way, with the same lemma list for bothdictionary and grammatical analyser/generator. This is especiallyimportant for small language communities, which lack the resourcesto uphold several parallel lexical databases.
Latent variable grammars take an observed (coarse) treebank and induce more fine-grained grammar categories, that are better suited for modeling the syntax of natural languages. Estimation can be done in a generative or a discriminative framework, and results in the best published parsing accuracies over a wide range of syntactically divergent languages and domains. In this paper we highlight the commonalities and the differences between the two learning paradigms. 1
Whereas the main phonological changes between OJ and NJ took place during the EMJ period, it was during the LMJ period that most of the significant grammatical changes took place which transformed Japanese from its premodern to its contemporary shape in both morphology and syntax. The course and precise dating of some changes is difficult to trace through the written sources; they are mainly observable in the sources dating from the end of the period. It may be no coincidence that sweeping changes took place during a period of civil war and great social upheaval and change which also would have resulted in a relaxation of social and linguistic norms.
A new Chinese chunking algorithm is proposed based on Naive Bayes model and semantic features. Through the analysis of Chinese chunking task, Naive Bayes model that combines different types of features were applied for its rapid performance of training and test. Semantic features were utilized to further improve the accuracy. Experimental results on the Chinese chunking corpus of Chinese Penn Treebank show that the algorithm achieves impressive accuracy of 92.8% in terms of the F-score.
This paper describes a first test run of Sentitext, a sentiment analysis system under development. Unlike most existing systems, Sentitext is entirely based on linguistic knowledge and independent of any domain, using a wide coverage lexical database and lacking learning algorithms or classifiers, strictly speaking. Results on this first test, for which a collection of hotel review texts from Tripadvisor has been used, are extremely encouraging, given the high polarity hit rate. Keywords: Sentiment analysis, opinion mining, on-line user reviews. 1 Introduccion *
Language is not a system of signs that allow the exchange of information among individuals but also the means to engage in intersubjective relationship as well as to mark the identity of the speaker: the connection between language and identity is often so strong that a single feature of linguistic usage can be enough to identity someone’s belonging in a certain group. The linguistic matrix, that consists of being aware of how linguistic register expectations become linguistic norms, constitutes the basis of the community of speakers and society. Linguistic behaviour is exposed to distinct social dynamics and new linguistic habits and can be influenced by the sense of belonging, as perceived by the speakers, and the strength of the language (vitality and prestige). Pluralinguistic formations make allowance for the different ways of communication, adapting them to local customs, in this way avoiding harm, as well as introducing a positive bias, in populations so far relegated to minority status.
The paper presents an approach to valency frame extraction for Croatian verbs on basis of morphological and syntactic features of wordforms from syntactically annotated sentences. We have used a gold standard sample of approximately 1200 sentences and 30.000 tokens from the Croatian Dependency Treebank and a frame instance extraction algorithm. We extracted 936 verb frame instances for 424 different verbs – consisting of lemmas, morphosyntactic tags and syntactic functions of the encountered wordforms – and manually assigned tectogrammatical functors to their elements. Distributional properties are given in terms of co-occurrences for each of these features. The obtained results will serve for further development of valency frame extraction procedures.
Recognition of special linguistic patterns in a certain language is very helpful for many NLP applications such as information extraction, machine translation and parsing. State-of-the-arts syntax parsers are based on given grammar. The used grammar is context free and cannot discover complex patterns which contain multiple linguistic units. We propose an unsupervised method to automatically discover the complex linguistic patterns from a classically parsed corpus. A specialized and efficient algorithm is applied to mine the frequent subtrees in the forest and the found subtrees are formalized as the linguistic patterns. The approach is validated on the Penn Chinese Treebank with found linguistic patterns.