Multilingual learning has been successful for other linguistic induction tasks such as lexicon acquisition, morphological segmentation, and part-of-speech tagging (Genzel, 2005; Snyder and Barzilay, 2008; Snyder et al., 2008; Snyder

lingual constituent, a sequence of part-of-speech tags is drawn from a language-specific distribution.

We treat the part-of-speech tag sequences of parallel sentences, as well as their

While this model is deficient —each observed subsequence of part-of-speech tags is generated many times over — its performance is far higher than that of unsupervised PCFGs.

In the next section we turn to the problem of inference under this model when only the part-of-speech tag sequences of parallel sentences and their word-level alignments are observed.

They have become the workhorse in almost all subareas and components of NLP, including part-of-speech tagging , chunking, named entity recognition and parsing.

Part-of-speech tags were used in the top-ranked systems in CoNLL 2003, as well as in many follow up studies that used the data set (Ando and Zhang 2005; Suzuki and Isozaki 2008).

LDC refers to the clusters created with the smaller LDC corpus and +pos indicates the use of part-of-speech tags as features.

The Top CoNLL 2003 systems all employed gazetteers or other types of specialized resources (e.g., lists of words that tend to co-occur with certain named entity types) in addition to part-of-speech tags .

Part-of-speech tags were assigned by a maximum entropy tagger trained on the Penn Tree-bank, and then simplified into seven categories: nouns, verbs, adverbs, adjectives, numbers, foreign words, and everything else.

Part-of-speech tags are not included in the dependency path.

Hearst (1992) used a small number of regular expressions over words and part-of-speech tags to find examples of the hypernym relation.

such as Ravichandran and Hovy (2002) and Pantel and Pennacchiotti (2006) use the same formalism of learning regular expressions over words and part-of-speech tags to discover patterns indicating a variety of relations.