| </term> and the decision of how to combine them | into | one or more <term> sentences </term> . In this | #1329 Sentence planning is a set of inter-related but distinct tasks, one of which is sentence scoping, i.e. the choice of syntactic structure for elementary speech acts and the decision of how to combine them into one or more sentences. | ||
| judges </term> . We reconceptualize the task | into | two distinct phases . First , a very simple | #1369 We reconceptualize the task into two distinct phases. | ||
| grammatical formalisms </term> can be translated | into | equivalent <term> RCGs </term> without increasing | #1644 In particular, range concatenation languages [RCL] can be parsed in polynomial time and many classical grammatical formalisms can be translated into equivalent RCGs without increasing their worst-case parsing time complexity. | ||
| example , after <term> translation </term> | into | an equivalent <term> RCG </term> , any <term> | #1660 For example, after translationinto an equivalent RCG, any tree adjoining grammar can be parsed in O(n6) time. | ||
| true text </term> through its transformation | into | the <term> noisy output </term> of an <term> | #2704 In this paper, we introduce a generative probabilistic optical character recognition (OCR) model that describes an end-to-end process in the noisy channel framework, progressing from generation of true text through its transformation into the noisy output of an OCR system. | ||
| create a <term> word-trie </term> , transform it | into | a <term> minimal DFA </term> , then identify | #3200 We create a word-trie, transform it into a minimal DFA, then identify hubs. | ||
| task , and gives them translingual reach | into | other <term> languages </term> by leveraging | #3627 It gives users the ability to spend their time finding more data relevant to their task, and gives them translingual reach into other languages by leveraging human language technology. | ||
| clusters </term> , offering us a good insight | into | the potential and limitations of semantically | #3962 A novel evaluation scheme is proposed which accounts for the effect of polysemy on the clusters, offering us a good insight into the potential and limitations of semantically classifying undisambiguated SCF data. | ||
| sequences </term> . We incorporate this analysis | into | a <term> diagnostic tool </term> intended for | #6049 We incorporate this analysis into a diagnostic tool intended for developers of machine translation systems, and demonstrate how our application can be used by developers to explore patterns in machine translation output. | ||
| basics of <term> SMT </term> : Theory will be put | into | practice . <term> STTK </term> , a <term> statistical | #6867 Theory will be put into practice. | ||
| other than <term> grammar </term> sensu stricto | into | the <term> treebank </term> . We argue that | #7846 Moreover, some examples are given that underline the necessity of integrating some kind of information other than grammar sensu stricto into the treebank. | ||
| </term> which takes these <term> features </term> | into | account . We introduce a new method for | #8121 The strength of our approach is that it allows a tree to be represented as an arbitrary set of features, without concerns about how these features interact or overlap and without the need to define a derivation or a generative model which takes these featuresinto account. | ||
| graphic interpretation system </term> that takes | into | account a variety of <term> communicative | #8703 It then presents an implemented graphic interpretation system that takes into account a variety of communicative signals, and an evaluation study showing that evidence obtained from shallow processing of the graphic's caption has a significant impact on the system's success. | ||
| features </term> that model these interactions | into | <term> discriminative log-linear models </term> | #10107 We show how to build a joint model of argument frames, incorporating novel features that model these interactions into discriminative log-linear models. | ||
| take <term> contextual information </term> | into | account . We evaluate our <term> paraphrase | #10237 We define a paraphrase probability that allows paraphrases extracted from a bilingual parallel corpus to be ranked using translation probabilities, and show how it can be refined to take contextual informationinto account. | ||
| language </term> to classify <term> GRs </term> | into | <term> frames </term> hierarchically in a way | #10329 It uses a powerful pattern-matching language to classify GRsinto frames hierarchically in a way that mirrors inheritance-based lexica. | ||
| Our work aims at providing useful insights | into | the the <term> computational complexity </term> | #10933 Our work aims at providing useful insights into the the computational complexity of those problems. | ||
| integrating automatic <term> Q/A applications </term> | into | real-world environments . <term> FERRET </term> | #12587 This paper describes FERRET, an interactive question-answering (Q/A) system designed to address the challenges of integrating automatic Q/A applicationsinto real-world environments. | ||
| <term> general-purpose NLP components </term> | into | a <term> machine translation pipeline </term> | #12736 The LOGON MT demonstrator assembles independently valuable general-purpose NLP componentsinto a machine translation pipeline that capitalizes on output quality. | ||
| interpreted directly without compilation | into | a <term> uniform grammar formalism </term> | #14060 A construction-specific approach also aids in task-specific language development by allowing a language definition that is natural in terms of the task domain to be interpreted directly without compilation into a uniform grammar formalism, thus greatly speeding the testing of changes to the language definition. |
