Communication is the key to success in any business. Whether you are trying to sell a
product, answer a query or complaint or convince your colleagues to adopt a certain
course of action, good communication often means the difference between success and
failure. At best, imprecise language, clumsy sentences or long-winded ‘waffle’, whether
in speech or writing, will give a poor impression of you or your business; at worst, what
you are trying to say will be misunderstood or ignored.
Sentiment analysis of citations in scientiﬁc papers and articles is a new and interesting problem due to the many linguistic differences between scientiﬁc texts and other genres. In this paper, we focus on the problem of automatic identiﬁcation of positive and negative sentiment polarity in citations to scientiﬁc papers. Using a newly constructed annotated citation sentiment corpus, we explore the effectiveness of existing and novel features, including n-grams, specialised science-speciﬁc lexical features, dependency relations, sentence splitting and negation features. ...
We investigate the problem of determining a compact underspecified semantical representation for sentences that may be highly ambiguous. Due to combinatorial explosion, the naive method of building semantics for the different syntactic readings independently is prohibitive. We present a method that takes as input a syntactic parse forest with associated constraintbased semantic construction rules and directly builds a packed semantic structure. The algorithm is fully implemented and runs in O(n4log(n)) in sentence length, if the grammar meets some reasonable 'normality' restrictions. ...
A revised and more structured version of Davey's discourse generation program has been implemented, which constructs the underlying forms for sentences and clauses by using rules which annotate and segment the initial sequence of events in various ways.
We present an algorithm for simultaneously constructing both the syntax and semantics of a sentence using a Lexicalized Tree Adjoining Grammar (LTAG). This approach captures naturally and elegantly the interaction between pragmatic and syntactic constraints on descriptions in a sentence, and the inferential interactions between multiple descriptions in a sentence. At the same time, it exploits linguistically motivated, declarative specifications of the discourse functions of syntactic constructions to make contextually appropriate syntactic choices. ...
Methods are presented within the parsing logic formulated by Cocke to reduce the large number of intermediate constructions produced and stored during the parsing of even moderately long sentences. A method is given for the elimination of duplicate construction codes stored for endocentric phrases of different lengths.
This paper proposes a novel method of building polarity-tagged corpus from HTML documents. The characteristics of this method is that it is fully automatic and can be applied to arbitrary HTML documents. The idea behind our method is to utilize certain layout structures and linguistic pattern. By using them, we can automatically extract such sentences that express opinion. In our experiment, the method could construct a corpus consisting of 126,610 sentences.
For German, most transformational lingusitic theories such as GB posit center-embedding as the underlying word order of sentences with embedded clauses: Weft ich [das Fahrrad zu reparieren] versprochen habe Because I the bike (ace) to repair promised have Because I promised to repair the bike However, far more common is a construction in which the entire subordinate clause is extraposed: Weil ich ti versprochen habe, [das Fahrrad zu reparieren]i.
In this paper, we describe a fast algorithm for aligning sentences with their translations in a bilingual corpus. Existing efficient algorithms ignore word identities and only consider sentence length (Brown el al., 1991b; Gale and Church, 1991). Our algorithm constructs a simple statistical word-to-word translation model on the fly during alignment. We find the alignment that maximizes the probability of generating the corpus with this translation model.
This paper describes a sentence generator that was built primarily to focus on syntactic form and syntactic relationships. Our main goal was to produce a tutorial system for the English language; the intended users of the system are people with language delaying handicaps such as deafness, and people learning English as a foreign language. For these populations, extensive exposure to standard English constructions (negatives, questions, relatlvization, etc.) and their interactions is necessary. ...
When machine translation (MT) knowledge is automatically constructed from bilingual corpora, redundant rules are acquired due to translation variety. These rules increase ambiguity or cause incorrect MT results. To overcome this problem, we constrain the sentences used for knowledge extraction to "the appropriate bilingual sentences for the MT." In this paper, we propose a method using translation literalness to select appropriate sentences or phrases.
The paper describes GEMS, a system for Generating and Expressing the Meaning of Sentences, focussing on the generation task, i.e. how GEMS extracts a set of propositional units from a knowledge store that can be expressed with a well-formed sentence in a target language. GEMS is lexically distributed. After a central processor has selected the first unit(s) from the knowledge store and activated the corresponding lexical entry, the further construction of the sentences meaning is entrusted to the entries in the vocabulary.
The dynamic interpretation of a formula as a binary relation (inducing transitions) on states is extended by alternative treatments of implication, universal quantification, negation and disjunction that are more "dynamic" (in a precise sense) than the usual reductions to tests from quantified dynamic logic (which, nonetheless, can be recovered from the new connectives). An analysis of the "donkey" sentence followed by the assertion "It will kick back" is provided.
We describe a computational system which parses discourses consisting of sequences of simple sentences. These contain a range of temporal constructions, including time adverbials, progressive aspect and various aspectual classes. In particular, the grammar generates the required readings, according to the theoretical analysis of (Glasbey, forthcoming), for sentence-final 'then'.
Every sentence has at least one verb. When you construct sentences, you have to pay
close attention to the verbs. You must choose the correct tense of the verb and make the
verb agree with its subject. The following discussion centers on these aspects of verbs. The
lesson ends with a review of some verb pairs that are especially troublesome.
The topics covered here describe the "meaningful chunks" of English sentence structure. In so doing they examine key grammatical principles underlying effective reading and writing. When discussing speech, we say we know something when we can...
Like English, Korean has different styles of speaking and writing that reflect the
genre, the setting, and the audience. A chat in a gym with a friend employs quite
different words and constructions than a news report to a national TV audience.
This chapter focuses on the use of sentence-final verb endings, whose selection is
sensitive to whether the genre is written or spoken, to whether the setting is
formal or informal, and to how close the speaker feels to the hearer.
Module đào tạo chung là phù hợp cho các ứng cử viên có nhu cầu tiếp tục nghiên cứu của họ chỉ cấp bằng tốt nghiệp. Tổng Module đào tạo cũng được sử dụng cho mục đích di trú đến Úc hoặc New Zealand, và cho sinh viên muốn hoàn thành giáo dục trung học của họ trong một quốc gia nói tiếng Anh. ARISON AND CONTRAST
In most essays and reports, you will need to refer to the cause of some particular situation and its effect. Note that, when constructing sentences, either the cause or the effect can be mentioned...
The discipline known as Mathematical Logic will not speciﬁcally be deﬁned within this text. Instead,
you will study some of the concepts in this signiﬁcant discipline by actually doing mathematical logic. Thus,
you will be able to surmise for yourself what the mathematical logician is attempting to accomplish.
Consider the following three arguments taken from the disciplines of military science, biology, and
set-theory, where the symbols (a), (b), (c), (d), (e) are used only to locate speciﬁc sentences....
West-facing (adj) Example: The front of the building faces west. It is a west-facing wall. Exercise 1: Complete the sentences :(Group 1) The back of the building..........
The long axis of the building is orientated east-west. The orientation of the long axis is east-west. Exercise 2: Complete the sentences: