Although most NLP researchers agree that a level of "logical form" is a necessary step toward the goal of representing the meaning of a sentence, few people agree on the content and form of this level of representation. An even smaller number of people have considered the complex action sentences that are often expressed in taskoriented dialogues. Most existing logical form representations have been developed for single-clause sentences that express assertions about properties or actual actions and in which time is not a main concern.
One problem for the generation of natural language text is determining when to use a sequence of simple sentences and when a single complex one is more appropriate. In this paper, we show how focus of attention is one factor that influences this decision and describe its implementation in a system that generates explanations for a student advisor expert system.
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.
Unit 1: Clause and sentence structure.
Simple sentences have one clause.
Clauses usually consist of a noun group as the subject, and a verb group.
Clauses can also have another noun group as the object or complement.
Clauses can have an adverbial, also called an adjunct.
Changing the order of the words in a clause can change its meaning.
Compound sentences consist of two or more main clauses. Complex sentences always include
a subordinate clause, as well as one or more main clauses....
We describe the strategy currently pursued for verbalising OWL ontologies by sentences in Controlled Natural Language (i.e., combining generic rules for realising logical patterns with ontology-speciﬁc lexicons for realising atomic terms for individuals, classes, and properties) and argue that its success depends on assumptions about the complexity of terms and axioms in the ontology.
Hierarchical HMM (HHMM) parsers make promising cognitive models: while they use a bounded model of working memory and pursue incremental hypotheses in parallel, they still achieve parsing accuracies competitive with chart-based techniques. This paper aims to validate that a right-corner HHMM parser is also able to produce complexity metrics, which quantify a reader’s incremental difﬁculty in understanding a sentence.
We propose a novel approach to translating from a morphologically complex language. Unlike previous research, which has targeted word inﬂections and concatenations, we focus on the pairwise relationship between morphologically related words, which we treat as potential paraphrases and handle using paraphrasing techniques at the word, phrase, and sentence level.
We consider the problem of answering complex questions that require inferencing and synthesizing information from multiple documents and can be seen as a kind of topicoriented, informative multi-document summarization. The stochastic, graph-based method for computing the relative importance of textual units (i.e. sentences) is very successful in generic summarization.
First of all, the criteria are described that are used to identify the elementary units of undering structure and the operations conoining them into complex units (Sect.l), t h e n t h e m a i n t y p e s o f ~ n ~ t s and o p e r a t i o n s resulting from an empirical investigation on t h e b a s i s o f t h e c r i t e r i a are registered ( S e c t . 2 ) ,...
We present a novel answer summarization method for community Question Answering services (cQAs) to address the problem of “incomplete answer”, i.e., the “best answer” of a complex multi-sentence question misses valuable information that is contained in other answers. In order to automatically generate a novel and non-redundant community answer summary, we segment the complex original multi-sentence question into several sub questions and then propose a general Conditional Random Field (CRF) based answer summary method with group L1 regularization....
We present a novel method for predicting inﬂected word forms for generating morphologically rich languages in machine translation. We utilize a rich set of syntactic and morphological knowledge sources from both source and target sentences in a probabilistic model, and evaluate their contribution in generating Russian and Arabic sentences. Our results show that the proposed model substantially outperforms the commonly used baseline of a trigram target language model; in particular, the use of morphological and syntactic features leads to large gains in prediction accuracy. ...
This paper describes a novel instancebased sentence boundary determination method for natural language generation that optimizes a set of criteria based on examples in a corpus. Compared to existing sentence boundary determination approaches, our work offers three signiﬁcant contributions. First, our approach provides a general domain independent framework that effectively addresses sentence boundary determination by balancing a comprehensive set of sentence complexity and quality related constraints.
A challenging problem for spoken dialog systems is the design of utterance generation modules that are fast, ﬂexible and general, yet produce high quality output in particular domains. A promising approach is trainable generation, which uses general-purpose linguistic knowledge automatically adapted to the application domain. This paper presents a trainable sentence planner for the MATCH dialog system.
The paper demonstrates that exponential complexities with respect to grammar size and input length have little impact on the performance of three unification-based parsing algorithms, using a wide-coverage grammar. The results imply that the study and optimisation of unification-based parsing must rely on empirical data until complexity theory can more accurately predict the practical behaviour of such parserQ. 1.
Methods of text compression in Navy messages are not limited to sentence fragments and the omissions of function words such as the copula be. Text compression is also exhibited within ~grammatieal" sentences and is identified within noun phrases in Navy messages. Mechanisms of text compression include increased frequency of complex noun sequences and also increased usage of nominalizations. Semantic relationships among elements of a complex noun sequence can be used to derive a correct bracketing of syntactic constructions. ...
We propose a method for analyzing long complex and compound sentences that utilizes global structure analysis with domain-specific pattern grammar. Previously, long sentence analysis with global information used the following methods: two-level analysis--global structure analysis of long sentences with domain-independent function words and parsing of their constituents[Doi et al., 1991], and pattern matching--adaptation of domain-specific fixed pattern to input sentences. By utilizing domaindependent information the latter method could analyze long sentences of that domain.
There are fifteen questions in part A. Forty percent are simple sentences,
others are complex sentences. All the words and phrases in the four answers are
grammatically correct when considered independently. But just only one’s is correct
about meaning. You should spend time to find out what type of structure is need to
form complete sentence. Don’t waste time to find the error in the answers.
Hoà hợp các thì (Sequence of tenses) Câu phức (Complex Sentence) là câu có một hoặc nhiều mệnh đề phụ. Chỉ cần nhớ một điều là Thì của động từ của mệnh đề phụ tùy thuộc Thì của động từ của mệnh đề chính .Dới đây là ví dụ minh hoạ cho sự hoà hợp các thì.