Sentence examples for deeper linguistic from inspiring English sources

"Words exist that can in principle resolve 20,000-year-old linguistic relationships," Dr. Pagel of Reading wrote in a recent symposium volume, "Time Depth in Historical Linguistics," adding that "words that can resolve even deeper linguistic relationships are not out of the question".

James W. Pennebaker, a social psychologist at the University of Texas who pioneered the text-analysis program often used in this kind of research, warns that positive and negative emotion words are the "low-hanging fruit" in such studies, and that deeper linguistic analysis should be explored to provide a "richer, more nuanced view" of how people present themselves to the world.

The semantic PropBank tags generated by SENNA, on the other hand, can easily be interpreted without deeper linguistic knowledge and used for a PAS-based relation extraction between biomedical entities.

Despite its importance for understanding the deep linguistic and social history of indigenous South America, the comparative linguistics of this major family is still in its early stages, with major questions regarding the internal classification of this family yet to be answered.

Building such tools requires deep linguistic knowledge, and we have people on the team expert in morphology and semantics.

In one enlightening episode the crossword composer Merl Reagle shares his thought processes while putting together a new puzzle, affording an insight into the deep linguistic structures that inform this seemingly trivial hobby.

To assess Graves's over-all accomplishment is a formidable undertaking, given both his prolificacy (more than a hundred books) and the breadth of his erudition (deep linguistic and historical research into a host of cultures, modern and ancient).

Seldom mentioned in the national education debate is a much broader and more intractable problem for which few solutions have been proposed: the deep linguistic divide that separates Hong Kong from the rest of China.

A distinguishing feature of the Stanford NLP Group is our effective combination of sophisticated and deep linguistic modeling and data analysis with innovative probabilistic, machine learning, and deep learning approaches to NLP.

One important example of this is the development of the head-driven phrase structure grammar (HPSG) formalism -- this is a way of analyzing natural language utterances that truly marries deep linguistic information with computer science mechanisms, such as unification and recursive data-types, for representing and propagating this information throughout the utterance's structure.

However, some languages, like Arabic, have deep linguistic differences resulting in poor cross domain performance.