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Implemented methods for proper names recognition rely on large gazetteers of common proper nouns and a set of heuristic rules (e.g. Mr. as an indicator of a PERSON entity type). …...

In this article, we apply to natural language parsing and tagging the device of trigger- pair predictors, previously employed exclu- sively within the field of language mod- elling for speech …...

Over the years, many proposals have been made to incorporate assorted types of feature in language models. However, discrepancies between training sets, evaluation criteria, algorithms, and hardware environments make it …...

In this paper, we described the PNNL Word Sense Disambiguation system as ap- plied to the English all-word task in Se- mEval 2007. We use a supervised learning approach, employing …...

In the application of Conditional Random Fields (CRF), a huge number of features is typically taken into ac- count. These models can deal with inter-dependent and correlated data with an …...

This paper describes a set of experi- ments on two sub-tasks of Quality Esti- mation of Machine Translation (MT) out- put. Sentence-level ranking of alternative MT outputs is done with …...

In this paper, we analyze relationships between word pairs and evaluate their idiosyncratic properties in the applied context of authorship attribution. Specifically, on three literary corpora we optimize word pair …...

AbstractWe take up the scientific question of what determines the preferred order of adjectives in English, in phrases such as big blue box where multiple adjectives modify a following noun. …...

Languages vary in their placement of multi- ple adjectives before, after, or surrounding the noun, but they typically exhibit strong intra- language tendencies on the relative order of those adjectives …...

AbstractAlthough it is widely agreed that world knowledge plays a significant role in quantifier scope disambiguation (QSD), there has been only very limited work on how to integrate this knowledge …...

AbstractIn-context learning (ICL) improves language models’ performance on a variety of NLP tasks by simply demonstrating a handful of examples at inference time. It is not well understood why ICL …...