Directional expressions cross-linguistically: Nanosyntax and lexicalization

Marina Pantcheva

doi:10.7557/12.214

Directional expressions cross-linguistically: Nanosyntax and lexicalization

Nordlyd ◽

10.7557/12.214 ◽

2010 ◽

Vol 36 (1) ◽

pp. pp

Author(s):

Marina Pantcheva

Keyword(s):

Syntactic Structure ◽

Spatial Domain ◽

Font Size ◽

Fine Grained

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Coconuts and curtain cakes: The production of wh-questions in ASD

Autism & Developmental Language Impairments ◽

10.1177/2396941520982953 ◽

2021 ◽

Vol 6 ◽

pp. 239694152098295

Author(s):

Nufar Sukenik ◽

Eléonore Morin ◽

Naama Friedmann ◽

Philippe Prevost ◽

Laurice Tuller

Keyword(s):

Error Analysis ◽

Language Disorder ◽

Syntactic Structure ◽

Autism Spectrum ◽

Production Rates ◽

Fine Grained ◽

Depth Analysis ◽

Wh Questions ◽

Analysis Of Error ◽

Error Types

Background and aims Children with autism spectrum disorders (ASD) have been found to exhibit difficulties in wh-question production. It is unclear whether these difficulties are pragmatic or syntactic in nature. The current study used a question elicitation task to assess the production of subject and object wh-questions of children with ASD in two different languages (Hebrew and French) wherein the syntactic structure of wh-questions is different, a fact that may contribute to better understanding of the underlying deficits affecting wh-question production. Crucially, beyond the general correct/error rate we also performed an in-depth analysis of error types, comparing syntactic to pragmatic errors and comparing the distribution of errors in the ASD group to that of children with typical development (TD) and children with Developmental Language Disorder (DLD). Results Correct production rates were found to be similar for the ASD and DLD groups, but error analysis revealed important differences between the ASD groups in the two languages and the DLD group. The Hebrew- and French ASD groups were found to produce pragmatic errors, which were not found in children with DLD. The pragmatic errors were similar in the two ASD groups. Syntactic errors were affected by the structure of each language. Conclusions Our results have shown that although the two ASD groups come from different countries and speak different languages, the correct production rates and more importantly, the error types were very similar in the two ASD groups, and very different compared to TD children and children with DLD. Implications: Our results highlight the importance of creating research tasks that test different linguistic functions independently and strengthen the need for conducting fine-grained error analysis to differentiate between groups and gain insights into the deficits underlying each of them.

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Sedimentary and tectonic setting of a mass-transport slope deposit in the Halifax Group, Halifax Peninsula, Nova Scotia, Canada

Atlantic Geology ◽

10.4138/atlgeol.2015.004 ◽

2015 ◽

Vol 51 (1) ◽

pp. 084 ◽

Cited By ~ 1

Author(s):

John W.F. Waldron ◽

Rebecca A. Jamieson ◽

Hayley D. Pothier ◽

Chris E. White

Keyword(s):

Nova Scotia ◽

Mass Transport ◽

Tectonic Setting ◽

Tectonic Deformation ◽

Font Size ◽

Fine Grained ◽

Metasedimentary Rocks ◽

Internal Structures ◽

Transport Direction ◽

Deformation Features

Fine-grained metasedimentary rocks of the Halifax Group in southern mainland Nova Scotia can be subdivided into mappable units. In Halifax Peninsula, sulphide-rich hornfels, black slate, metasiltstone, and metasandstone of the Cunard Formation are overlain by grey metasedimentary rocks with abundant cross-laminations and local carbonate and calc-silicate concretions, assigned to the Bluestone Quarry Formation. No fossils are known from the Bluestone Quarry Formation but lithological correlatives elsewhere are Tremadocian. The Bluestone Quarry Formation is here divided into four members. The lowest (Point Pleasant member) contains thin parallel-laminated and cross-laminated metasandstone beds with Bouma Tbcde and Tcde structures, and thicker beds with Bouma ‘a’ divisions. The Black Rock Beach member lacks the thicker massive beds and is dominated by rippled and cross-laminated metasedimentary rocks. The overlying Chain Rock member, an erosion-resistant ridge-forming unit, is disrupted by folds and boudinage. Bedding is truncated at the upper contact, and the internal structures are overprinted by (and therefore predate) the Neoacadian cleavage. They are interpreted as products of synsedimentary mass transport. Scarce folds in the Chain Rock member and current ripples in the underlying unit are consistent with a N or NW transport direction. The overlying Quarry Pond member consists of thinly bedded coherent metasedimentary rocks that generally resemble those of the Black Rock Beach member. Although there are indications of upward shallowing in equivalent successions elsewhere in the Halifax Group, the presence of a major mass transport deposit in the Bluestone Quarry Formation shows that this part of the Halifax Group was deposited on a submarine paleoslope. The failure of geologists to identify this feature in much-visited outcrops testifies to the difficulty of identifying synsedimentary deformation features that have been overprinted by later tectonic deformation.

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Probing the interaction of language contact and internal innovation

Studies in African Linguistics ◽

10.32473/sal.v48i1.114932 ◽

2019 ◽

Vol 48 (1) ◽

pp. 63-92

Author(s):

Hannah Gibson ◽

Lutz Marten

Keyword(s):

Language Contact ◽

Language Change ◽

Syntactic Structure ◽

External Factors ◽

East African ◽

Future Tense ◽

Morphological Form ◽

Fine Grained ◽

Bantu Language ◽

Internal And External Factors

The Bantu language Rangi is spoken at the northern borderlands of Tanzania, where Bantu, Cushitic and Nilotic languages meet. In many regards, Rangi exhibits the morphosyntax typically associated with East African Bantu: SVO word order, an extensive system of agreement and predominantly head-marking morphology. However, the language also exhibits a number of features which are unusual from a comparative and typological perspective, and which may have resulted from language contact. Four of these features are examined in detail in this paper: 1) Verb-auxiliary order found in the future tense, 2) clause-final negation, 3) a three-way distinction in verbal deictic markers, and 4) an inclusive/exclusive distinction in personal possessive pronouns. These features are assessed with reference to three criteria: syntactic structure, lexical/morphological form and geographic distribution. The examination shows that two of the unusual features result from a combination of internal and external factors, while the other two appear not to be related to external influence through contact. The results of the study show the complex interaction between internal and external factors in language change, and the importance of investigating potentially contact-induced change in detail to develop a more complex and fine-grained understanding of the morphosyntactic process of innovation involved.

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Syntactically Meaningful and Transferable Recursive Neural Networks for Aspect and Opinion Extraction

Computational Linguistics ◽

10.1162/coli_a_00362 ◽

2020 ◽

Vol 45 (4) ◽

pp. 705-736

Author(s):

Wenya Wang ◽

Sinno Jialin Pan

Keyword(s):

Neural Network ◽

Neural Networks ◽

Syntactic Structure ◽

Feature Learning ◽

Single Domain ◽

Fine Grained ◽

Adversarial Network ◽

Dependency Tree ◽

Recursive Neural Networks ◽

Syntactic Relations

In fine-grained opinion mining, extracting aspect terms (a.k.a. opinion targets) and opinion terms (a.k.a. opinion expressions) from user-generated texts is the most fundamental task in order to generate structured opinion summarization. Existing studies have shown that the syntactic relations between aspect and opinion words play an important role for aspect and opinion terms extraction. However, most of the works either relied on predefined rules or separated relation mining with feature learning. Moreover, these works only focused on single-domain extraction, which failed to adapt well to other domains of interest where only unlabeled data are available. In real-world scenarios, annotated resources are extremely scarce for many domains, motivating knowledge transfer strategies from labeled source domain(s) to any unlabeled target domain. We observe that syntactic relations among target words to be extracted are not only crucial for single-domain extraction, but also serve as invariant “pivot” information to bridge the gap between different domains. In this article, we explore the constructions of recursive neural networks based on the dependency tree of each sentence for associating syntactic structure with feature learning. Furthermore, we construct transferable recursive neural networks to automatically learn the domain-invariant fine-grained interactions among aspect words and opinion words. The transferability is built on an auxiliary task and a conditional domain adversarial network to reduce domain distribution difference in the hidden spaces effectively in word level through syntactic relations. Specifically, the auxiliary task builds structural correspondences across domains by predicting the dependency relation for each path of the dependency tree in the recursive neural network. The conditional domain adversarial network helps to learn domain-invariant hidden representation for each word conditioned on the syntactic structure. In the end, we integrate the recursive neural network with a sequence labeling classifier on top that models contextual influence in the final predictions. Extensive experiments and analysis are conducted to demonstrate the effectiveness of the proposed model and each component on three benchmark data sets.

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Fast priming of grammatical decisions: repetition and transposed-word priming effects

Royal Society Open Science ◽

10.1098/rsos.211082 ◽

2022 ◽

Vol 9 (1) ◽

Author(s):

Jonathan Mirault ◽

Mathieu Declerck ◽

Jonathan Grainger

Keyword(s):

Sentence Processing ◽

Repetition Priming ◽

Syntactic Structure ◽

Decision Task ◽

Target Sequence ◽

Font Size ◽

Prime Word ◽

Priming Effects ◽

Word Sequence ◽

Word Priming

We used the grammatical decision task to investigate fast priming of written sentence processing. Targets were sequences of 5 words that either formed a grammatically correct sentence or were ungrammatical. Primes were sequences of 5 words and could be the same word sequence as targets, a different sequence of words with a similar syntactic structure, the same sequence with two inner words transposed or the same sequence with two inner words substituted by different words. Prime-word sequences were presented in a larger font size than targets for 200 ms and followed by the target sequence after a 100 ms delay. We found robust repetition priming in grammatical decisions, with same sequence primes leading to faster responses compared with prime sequences containing different words. We also found transposed-word priming effects, with faster responses following a transposed-word prime compared with substituted-word primes. We conclude that fast primed grammatical decisions might offer investigations of written sentence processing what fast primed lexical decisions have offered studies of visual word recognition.

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Improving Fine-Grained Opinion Mining Approach with a Deep Constituency Tree-Long Short Term Memory Network and Word Embedding

Recent Advances in Computer Science and Communications ◽

10.2174/2666255813999200922142212 ◽

2020 ◽

Vol 13 ◽

Author(s):

Dalila Bouras ◽

Mohamed Amroune ◽

Hakim Bendjenna ◽

Issam Bendib

Keyword(s):

Opinion Mining ◽

Short Term Memory ◽

State Of The Art ◽

Syntactic Structure ◽

Product Reviews ◽

Short Term ◽

Term Memory ◽

Fine Grained ◽

Wide Range ◽

Long Short Term Memory

Objective: One key task of fine-grained opinion mining on product review is to extract product aspects and their corresponding opinion expressed by users. Previous work has demonstrated that precise modeling of opinion targets within the surrounding context can improve performances. However, how to effectively and efficiently learn hidden word semantics and better represent targets and the context still needs to be further studied. Recent years have seen a revival of the long short-term memory (LSTM), with its effectiveness being demonstrated on a wide range of problems. However, LSTM based approaches are still limited to linear data processing since it processes the information sequentially. As a result, they may perform poorly on user-generated texts, such as product reviews, tweets, etc., whose syntactic structure is not precise.To tackle this challenge, Methods: In this research paper, we propose a constituency tree long short term memory neural network-based approach. We compare our model with state-of-the-art baselines on SemEval 2014 datasets. Results: Experiment results show that our models obtain competitive performances compared to various supervised LSTM architectures. Conclusion: Our work contributes to the improvement of state-of-the-art aspect-level opinion mining methods and offers a new approach to support human decision-making process based on opinion mining results.

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An argument for phrasal spell-out: Indefinites and interrogatives in Spanish

Nordlyd ◽

10.7557/12.218 ◽

2009 ◽

Vol 36 (1) ◽

pp. pp ◽

Cited By ~ 1

Author(s):

Antonio Fábregas

Keyword(s):

Syntactic Structure ◽

Lexical Item ◽

Font Size ◽

Indefinite Pronouns

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Classical Armenian declension

Nordlyd ◽

10.7557/12.220 ◽

2009 ◽

Vol 36 (1) ◽

pp. pp

Author(s):

Pavel Caha

Keyword(s):

Linear Order ◽

Font Size ◽

Fine Grained ◽

Core Components ◽

Analytic Expression ◽

Core Part

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Application of an image management system in microscopy

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100129899 ◽

1992 ◽

Vol 50 (2) ◽

pp. 1052-1053

Author(s):

Richard S. Chemock

Keyword(s):

Data Storage ◽

Cost Savings ◽

Image Data ◽

Analytical Techniques ◽

Operational Mode ◽

Fine Grained ◽

Image Recording ◽

Primary Output ◽

Capacity Data ◽

Image Management System

One of the most common tasks in a typical analysis lab is the recording of images. Many analytical techniques (TEM, SEM, and metallography for example) produce images as their primary output. Until recently, the most common method of recording images was by using film. Current PS/2R systems offer very large capacity data storage devices and high resolution displays, making it practical to work with analytical images on PS/2s, thereby sidestepping the traditional film and darkroom steps. This change in operational mode offers many benefits: cost savings, throughput, archiving and searching capabilities as well as direct incorporation of the image data into reports.The conventional way to record images involves film, either sheet film (with its associated wet chemistry) for TEM or PolaroidR film for SEM and light microscopy. Although film is inconvenient, it does have the highest quality of all available image recording techniques. The fine grained film used for TEM has a resolution that would exceed a 4096x4096x16 bit digital image.

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Use of fractals to describe microstructures of porous thick-film platinum electrodes

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100121971 ◽

1992 ◽

Vol 50 (1) ◽

pp. 314-315

Author(s):

Steven D. Toteda

Keyword(s):

Fractal Dimension ◽

Power Plants ◽

Electrical Response ◽

Cubic Phase ◽

Platinum Electrodes ◽

Fine Grained ◽

Impedance Response ◽

Platinum Particles ◽

Energy Surfaces ◽

Highly Porous

Zirconia oxygen sensors, in such applications as power plants and automobiles, generally utilize platinum electrodes for the catalytic reaction of dissociating O2 at the surface. The microstructure of the platinum electrode defines the resulting electrical response. The electrode must be porous enough to allow the oxygen to reach the zirconia surface while still remaining electrically continuous. At low sintering temperatures, the platinum is highly porous and fine grained. The platinum particles sinter together as the firing temperatures are increased. As the sintering temperatures are raised even further, the surface of the platinum begins to facet with lower energy surfaces. These microstructural changes can be seen in Figures 1 and 2, but the goal of the work is to characterize the microstructure by its fractal dimension and then relate the fractal dimension to the electrical response. The sensors were fabricated from zirconia powder stabilized in the cubic phase with 8 mol% percent yttria. Each substrate was sintered for 14 hours at 1200°C. The resulting zirconia pellets, 13mm in diameter and 2mm in thickness, were roughly 97 to 98 percent of theoretical density. The Engelhard #6082 platinum paste was applied to the zirconia disks after they were mechanically polished ( diamond). The electrodes were then sintered at temperatures ranging from 600°C to 1000°C. Each sensor was tested to determine the impedance response from 1Hz to 5,000Hz. These frequencies correspond to the electrode at the test temperature of 600°C.

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