Top PDF Sentence Structure/Sentence Types HANDOUT

Sentence Structure/Sentence Types HANDOUT

Sentence Structure/Sentence Types HANDOUT

Such sentences will contain a transitive verb (since there is a DO). OC = object complement; it tells you what is being implicitly predicated about the DO. [Note: grammarians also label the OC as a predicate accusative--if that’s helpful to you!] The “(A or N)” notation above indicates that the OC can be either an adjective or a noun. In these types of sentences, there is an implied copular relationship between the DO and the OC. Exx.:

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Word Order Role In The Development Of Sentence Informational Structure In The Ergative Languages Of Dagestan

Word Order Role In The Development Of Sentence Informational Structure In The Ergative Languages Of Dagestan

In this regard, it makes sense to turn to the experience of a subject universal definition, proposed by Edward Keenan, which justifies the insolvability of a subject unified definition problem for all languages and even for all types of sentences of the same language. There are no functionally equivalent subjects in each specific language and even in different sentences of one language. The syntactic properties of the subject are mandatory in some languages, and they may be optional for others. Therefore, the scale of the subject similarity is proposed [Keenan 1982: 252]. The essence of this approach is that E. Keenan uses the multifactor approach to determine a subject, based on the identification of all subject properties that are found in the basic sentences. The scale of subject similarity is composed of these properties. The nominal terms of a sentence, which have all the potential properties of subjects, are as close as possible to an ideal subject. And vice versa: the nominal terms of a sentence, which have the minimum properties of subjects or do not have them at all, are as far from an ideal subject as possible.
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SENTENCE STRUCTURE. An independent clause can be a complete sentence on its own. It has a subject and a verb.

SENTENCE STRUCTURE. An independent clause can be a complete sentence on its own. It has a subject and a verb.

Every complete sentence contains two parts: a subject and a predicate. The subject is what (or who) the sentence is about, while the predicate tells something about the subject. A sentence begins with a capital letter and ends with a period, a question mark, or an exclamation point. The different types of sentences are identified by how they are constructed and by how they express thoughts. Good writers use a mixture of different sentence structures in their writing. Varying sentences makes writing more colorful and interesting.

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Verb Argument Structure Alternations in Word and Sentence Embeddings

Verb Argument Structure Alternations in Word and Sentence Embeddings

Further previous studies on which types of information are contained in embeddings in- clude Bjerva and Augenstein (2018), which asked whether certain phonological, morphological and syntactic information can be extracted from lan- guage embeddings. Malaviya et al. (2017) pre- dicted features from language embeddings which were trained as part of an ANN for machine trans- lation. Finally, ¨Ostling and Tiedemann (2017) learned language embeddings via multilingual lan- guage modeling and used them to reconstruct ge- nealogical trees. However, we are interested in word or sentence embeddings. Extracting infor- mation from word embeddings is a common task in natural language processing. While most NLP research is application-oriented and directly or in- directly focuses on obtaining embeddings which contain as much knowledge about the task at hand as possible (e.g., by varying the training corpus or embedding method), we are interested in the ques- tion how much information is trivially contained in selected popular embeddings.
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Towards Establishing a Hierarchy in the Japanese Sentence Structure

Towards Establishing a Hierarchy in the Japanese Sentence Structure

SCT is a small logical language that attempts to approximate the dependency structures in natural language by constraining management of scopes. It stems from the sequence semantics of Vermeulen (1993) and the static setup of Dynamic Semantics by Dekker (2002) and Cresswell (2002). The theory tries to explain what is accepted as grammatically correct and what is not on the basis of formal semantics: a sentence is grammatically valid if and only if it can successfully pass through the process of interpretation or semantic evaluation. It has been proven that SCT can give a unified account of various types of linguistic data from unrelated languages, e.g., English, French, Japanese, and Tukang Besi (Indonesia).
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Mixed Sentence Structure Problem: Double Verb Error

Mixed Sentence Structure Problem: Double Verb Error

Often the easiest way to fix a double verb error is to add a relative pronoun (such as “that, which, or who”) so that you create a new subject for one of the verbs. The example problem sentence at the beginning of this handout can be fixed in this way.

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Causative Sentence Characteristic’s Based on Its Semantic-Structure

Causative Sentence Characteristic’s Based on Its Semantic-Structure

The paper discuses the basic characteristics of the causative connectors based on the Albanian scholars. The Albania scholar Floqi has divided in seven types the causative sentence characteristic’s based on its semantic-structure: a) direct causative sentences; b) argumentative causative sentences of conclusion; c) argumentative causative sentences of order; d) causative sentences of conditional saying; e) additional and middle causative sentences; f) evaluative causative sentences; g) feelings (emotional) causative sentences. The causative sentences are grouped based on the connector that connects the two sentences, one of the sentences is the main one and the other is the subordinate one.
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Identification of sentence types for writing skill in teacher education

Identification of sentence types for writing skill in teacher education

Learning how to write impactful sentences is an important skill that takes practice that requires discrimination of four types of sentences because sentence structure is a central aspect of every sentence. Once the learners are aware of the different types of sentences and their constructional parts, they can then choose the most helpful type of sentences for the expression of their ideas and can grow them into paragraphs, compositions, and essays by correctly punctuate them. Moreover, understanding of possible problems with sentence such as run-on sentences, fused sentences and comma splices, loose sentences, choppy sentences, and the like are highly essential. Students can appropriately express themselves more clearly in writing when they master how to identify and write the four basic types of sentences along with to placement of appropriate punctuation intra-sententially and word-finally, which make the ideas they are expressing in their writing better understood by the reader.
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Complex sentence as a structure for representing knowledge

Complex sentence as a structure for representing knowledge

The examples from our sample contain three types of indexicals, the tense, the as- pect, and the conjunction when. Since there is no tense variation affecting the interpreta- tion of the sentence, this indexical is not considered here. As for the morphosyntactic category of aspect, within the framework of the Cognitive Theory of Tense and Aspect (CTTA) (Kravchenko, 1990; 1992; 1997) its cognitive content is related to the contrast between two basic concepts of events: verbal referents are categorized either as those identified empirically (through direct observation), or those identified on the basis of existing (background) knowledge. These concepts reflect the two modes of knowledge representation mentioned above, phenomenological and structural, which are based on cognitively different channels for data input. These different types of input may be prag- matically interpreted as “observer’s competence/knowledge” and “speaker’s competence/ knowledge”.
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The Taxonomy of the Functional and Structural Uses  of Adverbs in Business Letter Writing  in English

The Taxonomy of the Functional and Structural Uses of Adverbs in Business Letter Writing in English

The findings confirm that the ESL users or learners master the use of adverbs in English at the surface level without understanding the deep level implications and nuances. Their use of adverbs shows a confused or ambiguous qualified or quantified relationship with an action denoted by a verb or its equivalent in contrast to consider ‘adverbial emphasis as a receptive intensification’ (Pérez-Paredes and Díez-Bedmar, 2012). Compared to meaning and function based use of the adverbs, the sentence or linguistic structure based use of adverbs lack diversity. As Zi-hong (2010) stated, the difficulty of capturing the rhetorical repositioning while “learning or acquiring the syntactic positions of adverbs in English” (p. 50) is identified in this research. The average number of the total respondents reveals that generally the students use minimum four to five adverbs in their letter consisting around 120 words in average. It seems acceptable. However, when a sample of seven selected scripts based on the score obtained progressively revealed that the average is almost eight adverbs. However, as mentioned before, they lack diversity of types and functions.
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Teaching ecuadorian efl university students academic writing utilizing sentence structure formulas

Teaching ecuadorian efl university students academic writing utilizing sentence structure formulas

exploratory sequential mixed methods study investigated the effects of using sentence structure formulas to teach EFL university students basic academic writing skills. Thirty level B2 EFL students from an Ecuadorian university participated in this research. Two types of data were collected and ve and quantitative data. Qualitative data were gathered through semi- uantitative data were collected through opinion academic essays administered both at the beginning and at the end of a pedagogical intervention using sentence structure formulas. Findings revealed that assisting academic writing with sentence structure formulas helps EFL students structured academic essays. Three major positive effects were found: 1) use of more tterns in academic essays, 2) less errors with complements of ors. The results showed that pedagogical interventions focused be applied as a first stage in the process of teaching academic writing. Participants said that they felt more confident to write academic essays after they were taught the different sentence structure formulas, both based on punctuation and on the six types of verbs that his study suggests that EFL learners may benefit from focusing on sentence structure formulas when they are at the onset of their academic writing learning
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GRAPH PATTERN MATCHING IN YEAST DATASET

GRAPH PATTERN MATCHING IN YEAST DATASET

Conjunctions, combining two ASL sentences is different based on the conjunction needed. For example the concept of the word AND does not exist in ASL. Sign a sentence, take short pause, and then sign the next sentence. While conjunctions such as OR and BUT have signs. Interjections like WOW! or OH! can be fingerspelled or they may have a sign like WOW. They are usually made into a separate statement. While Prepositions are not used in ASL, because they are shown in context.

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Sentence Length

Sentence Length

The distribution of sentence length in ordi- nary language is not well captured by the ex- isting models. Here we survey previous mod- els of sentence length and present our random walk model that offers both a better fit with the data and a better understanding of the dis- tribution. We develop a generalization of KL divergence, discuss measuring the noise inher- ent in a corpus, and present a hyperparameter- free Bayesian model comparison method that has strong conceptual ties to Minimal Descrip- tion Length modeling. The models we obtain require only a few dozen bits, orders of mag- nitude less than the naive nonparametric MDL models would.
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Recognizing Sublanguages in Scientific Journal Articles through Closure Properties

Recognizing Sublanguages in Scientific Journal Articles through Closure Properties

It has been suggested since Harris’s classic work (Harris et al., 1989) that scientific writing forms a sublanguage. However, it is also clear from the work of (Stetson et al., 2002) and (Mi- haila et al., 2012) that some putative sublanguages are a better fit to the model than others, and to date there has been no publicly available, repeatable method for assessing the fit of a set of documents to the sublanguage model. This paper presents the first such package of software and uses it to evaluate two corpora of scientific journal articles. Future work will include evaluating the effects of mapping all numbers to a fixed NUMBER token, which might affect the tendencies towards lexi- cal closure; evaluating the effect of the size of tag sets on type/part-of-speech ratios, which might affect tendencies towards type/part-of-speech clo- sure; and seeking a way to introduce more syntac- tic structure into the sentence type analysis with- out losing the generality of the current approach. We will also apply the technique to other biomed- ical genres, such as clinical documents. There is also an important next step to take—this work provides a means for recognizing sublanguages, but does not tackle the problem of determining their characteristics. However, despite these limi- tations, this paper presents a large step towards fa- cilitating the study of sublanguages by providing a quantitative means of assessing their presence.
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SEPTEMBER Unit 1 Page Learning Goals 1 Short a 2 b 3-5 blends 6-7 c as in cat 8-11 t p

SEPTEMBER Unit 1 Page Learning Goals 1 Short a 2 b 3-5 blends 6-7 c as in cat 8-11 t p

Irregular Verbs, Vocabulary, Sentence Types 66. Parts Of Speech, Vocabulary.[r]

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Style.ppt

Style.ppt

of words in a sentence, types of sentences, number of syllables in words.. You can.[r]

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A Case Study of Modeling Technique on Building a Smart Chinese International Learning Environment

A Case Study of Modeling Technique on Building a Smart Chinese International Learning Environment

completed the self-adapting education system concerning complex sentence types. It will continue to construct all other self-adapting systems for International Chinese language learning, hoping to achieve effective construction of a complete learning environment for Smart Chinese Learning. With the help of the Learning analytics technology, teachers have more opportunity to discover the real learning situation of each student. The Smart Learning environment can help students to assess their academic progress, predict their future performance, discover their potential problems and get suggestions. Therefore, Smart Learning can provide high-quality, personalized educational services to every student and raise intelligent, well educated people.
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Inducing Sentence Structure from Parallel Corpora for Reordering

Inducing Sentence Structure from Parallel Corpora for Reordering

The language processing community actively works on the problem of automatically inducing grammat- ical structure from a corpus of text (Pereira and Schabes, 1992). Some success in this area has been demonstrated via generative models (Klein and Manning, 2002), which often benefit from well- chosen priors (Cohen and Smith, 2009) or poste- rior constraints (Ganchev et al., 2009). In princi- ple, these models must discover the syntactic pat- terns that govern a language from the sequences of word tokens alone. These models are often evalu- ated relative to reference treebank annotations.

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Sentence Patterns.ppt

Sentence Patterns.ppt

Exercise 3- Convert the below mentioned interrogative sentences into the other three types (if possible):.. • Have you ever seen a flying fish![r]

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Improving Neural Abstractive Document Summarization with Structural Regularization

Improving Neural Abstractive Document Summarization with Structural Regularization

In this paper we analyze and verify the neces- sity of leveraging document structure in docu- ment summarization, and explore the effective- ness of capturing structural properties of docu- ment summarization by importing both structural- compression and structural-coverage regulariza- tion based on the proposed hierarchical encoder- decoder with hybrid attention model. Experimen- tal results demonstrate that the structural regular- ization enables our model to generate more in- formative and concise summaries by enhancing sentences compression and coverage. Our model achieves considerable improvement over state-of- the-art seq2seq-based abstractive methods, espe- cially on long document with long summary. Acknowledgments
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