The most powerful and the most perfect expression of thought and feeling through the
medium of oral language must be traced to the mastery of words. Nothing is better suited to
lead speakers and readers of English into an easy control of this language than the command
of the phrase that perfectly expresses the thought. Every speaker‟s aim is to be heard and
understood. A clear, crisp articulation holds an audience as by the spell of some irresistible
This is a reproduction of a book published before 1923. This book may have occasional imperfections such as missing or blurred pages, poor pictures, errant marks, etc. that were either part of the original artifact, or were introduced by the scanning process. We believe this work is culturally important, and despite the imperfections, have elected to bring it back into print as part of our continuing commitment to the preservation of printed works worldwide. We appreciate your understanding of the imperfections in the preservation process, and hope you enjoy this valuable book....
How to Write a Letter of Recommendation for Graduate School Admissions presents abouts tips on writing letter of recommendation; general outline of the recommendation letter; dos and don’ts for recommendation letters; questions and answers for recommendation letters; useful phrases for recommendation letters; writing your own letter of recommendation.
The goal of "500 Real English Phrases" is to teach you English phrases (not just individual English words) that you can use in many different situations. The phrases selected for "500 Real English Phrases" are typical expressions used by native speakers.
There is an index with pronunciation for all the key vocabulary, a table of phonetic symbols, and an answer key at the end of this book. The book focuses not just on single words, hut on useful phrases and collocations. For example, difficult teaching points such as the difference between do and make.
The book focuses not just on single words, hut on useful phrases and collocations. For example, difficult teaching points such as the difference between do and make are dealt with through collocation (we do our homework, but we make mistakes}, and useful phrases (e.g., come over, in the unit on come) are presented.
Simultaneous actions described by absolute phrases:
An absolute phrase consists of a head - word (often a
noun) plus at least one other word. Note that the head
word in the absolute phrase denotes something which is a
part of, or belong to the thing or person that is the subject
of the finite verb of the sentence.
This paper describes novel and practical Japanese parsers that uses decision trees. First, we construct a single decision tree to estimate modification probabilities; how one phrase tends to modify another. Next, we introduce a boosting algorithm in which several decision trees are constructed and then combined for probability estimation. The two constructed parsers are evaluated by using the EDR Japanese annotated corpus. The single-tree method outperforms the conventional .Japanese stochastic methods by 4%. ...
Resolving polysemy and synonymy is required for high-quality information extraction. We present ConceptResolver, a component for the Never-Ending Language Learner (NELL) (Carlson et al., 2010) that handles both phenomena by identifying the latent concepts that noun phrases refer to. ConceptResolver performs both word sense induction and synonym resolution on relations extracted from text using an ontology and a small amount of labeled data. Domain knowledge (the ontology) guides concept creation by deﬁning a set of possible semantic types for concepts.
An efﬁcient decoding algorithm is a crucial element of any statistical machine translation system. Some researchers have noted certain similarities between SMT decoding and the famous Traveling Salesman Problem; in particular (Knight, 1999) has shown that any TSP instance can be mapped to a sub-case of a word-based SMT model, demonstrating NP-hardness of the decoding task. In this paper, we focus on the reverse mapping, showing that any phrase-based SMT decoding problem can be directly reformulated as a TSP.
The use of phrases in retrieval models has been proven to be helpful in the literature, but no particular research addresses the problem of discriminating phrases that are likely to degrade the retrieval performance from the ones that do not. In this paper, we present a retrieval framework that utilizes both words and phrases ﬂexibly, followed by a general learning-to-rank method for learning the potential contribution of a phrase in retrieval.
Statistical parsing of noun phrase (NP) structure has been hampered by a lack of goldstandard data. This is a signiﬁcant problem for CCGbank, where binary branching NP derivations are often incorrect, a result of the automatic conversion from the Penn Treebank.(N (N/N lung) (N (N/N cancer) (N deaths) ) )This structure is correct for most English NPs and is the best solution that doesn’t require manual reannotation. However, the resulting derivations often contain errors.
In this paper we describe a novel data structure for phrase-based statistical machine translation which allows for the retrieval of arbitrarily long phrases while simultaneously using less memory than is required by current decoder implementations. We detail the computational complexity and average retrieval times for looking up phrase translations in our sufﬁx array-based data structure. We show how sampling can be used to reduce the retrieval time by orders of magnitude with no loss in translation quality. ...
This paper describes a spelling correction system that functions as part of an intelligent tutor that carries on a natural language dialogue with its users. The process that searches the lexicon is adaptive as is the system filter, to speed up the process. The basis of our approach is the interaction between the parser and the spelling corrector. Alternative correction targets are fed back to the parser, which does a series of syntactic and semantic checks, based on the dialogue context, the sentence context, and the phrase context. phrases that are used in the correction process. ...
We present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. Our unsupervised approach uses a heuristic based on attachment proximity and trains from raw text that is annotated with only part-of-speech tags and morphological base forms, as opposed to attachment information. It is therefore less resource-intensive and more portable than previous corpus-based algorithm proposed for this task. ...
Ill this paper we describe a neural network-based approach to prepositional phrase attachment disambiguation for real world texts. Although the use of semantic classes in this task seems intuitively to be adequate, methods employed to date have not used them very effectively. Causes of their poor results are discussed. Our model, which uses only classes, scores appreciably better than the other class-based methods which have been tested on the Wall Street Journal corpus. To date, the best result obtained using only classes was a score of 79.1%; we obtained an accuracy score of 86.8%. ...
While various aspects of syntactic structure have been shown to bear on the determination of phraselevel prosody, the text-to-speech field has lacked a robust working system to test the possible relations between syntax and prosody. We describe an implemented system which uses the deterministic parser Fidditch to create the input for a set of prosody rules.
Several attempts have been made to learn phrase translation probabilities for phrasebased statistical machine translation that go beyond pure counting of phrases in word-aligned training data. Most approaches report problems with overﬁtting. We describe a novel leavingone-out approach to prevent over-ﬁtting that allows us to train phrase models that show improved translation performance on the WMT08 Europarl German-English task.