Sentence examples for in addition to the words from inspiring English sources

On the bench, his view has been that the Court is obligated to consider the evolving standards of society — the constitution with a small "c" — in addition to the words of the Constitution, which are what matter to Scalia.

In addition to the words of the artist herself, "Marina Abramovic the Artist Is Present" collects testimony from art historians, dealers and curators, notably Klaus Biesenbach, the enthusiastic impresario of the MoMA show, who likens working with Ms. Abramovic to a love affair.

In addition to the words noted, a seemingly insignificant phrase appears throughout both HFA and SFDRR, "as appropriate".

To ensure that all relevant studies were retrieved, a second series of searches was performed with the names of the retained questionnaires as search terms in addition to the words "rheumatoid arthritis" and references of included studies and studies citing the original article were manually searched using Scopus citation tracker.

In addition to the word-based and POS-based bigram and trigram models, class-based language models can be optionally used [46].

The proposed method includes NLP tasks for text preprocessing and learning word representation features from a large amount of raw text data, in addition to the word, the word n-gram, the character n-gram, and the traditional orthographic information (baseline features) for feature extraction, and applies CRF for token labeling.

Since the size of this edition of the corpus was not enough for making a reliable word-based n-gram language model, we built POS-based and class-based n-gram language models, in addition to the word-based n-gram model.

In addition to the word "debt," the smaller number who expressed support for raising the debt limit were most likely to use the words "default," "economy" and "country".

In addition to the word-naming experiment, a test known as the Een-Minuut-Test (One-Minute Test (EMT)) by Brus and Voeten (1973) was used to assess reading decoding or reading fluency.

However, if we represent a click-word in the context of all the features that we defined above, our proposed model can make a prediction based on the learned click-word characteristics (e.g. a word's semantic type) in addition to the word itself, making it much more robust when handling new/unseen words.

The reason why Experiment 8 is not outperforming Experiment 7 is most likely because Experiment 8 is using unique words found in the corpus in addition to the unique words found in Experiment 7. As Table 10 shows, around 1100 new words are added to the vocabulary in Experiment 8 compared to Experiment 7 for all set conditions without reducing the OOV rate significantly.