A large number of false negatives on the part of O-CRF can be attributed to its lack of lexical features, which are often crucial when part-of-speech tagging errors are present.

nize the positive instance, despite the incorrect part-of-speech tag.

The set of features used by O-CRF is largely similar to those used by O-NB and other state-of-the-art relation extraction systems, They include part-of-speech tags (predicted using a separately trained maximum-entropy model), regular expressions (e. g.detecting capitalization, punctuation, eta), context words, and conjunctions of features occurring in adjacent positions within six words to the left and six words to the right of the current word.

O-CRF was built using the CRF implementation provided by MALLET (McCallum, 2002), as well as part-of-speech tagging and phrase-chunking tools available from OPENNLP.2

We use the OpenNLP toolkit6 for segmentation and part-of-speech tagging.

Hierarchy 1911 1987 Class 8 8 Section 39 39 Subsection 97 95 Head Group 625 596 Head 1044 990 Part-of-speech 3934 3220 Paragraph 10244 6443 Semicolon Group 43196 59915 Total Words 98924 225 124 Unique Words 59768 100470

The part-of-speech level is a little confusing, since clearly no such grouping contains an exhaustive list of all nouns, all verbs etc.

We will write “POS” to indicate a structure in Roget’s and “part-of-speech” to indicate the word category in general.

In the future, we hope to apply similar multilingual models to other core unsupervised analysis tasks, including part-of-speech tagging and grammar induction, and to further investigate the role that language relatedness plays in such models.

The accuracy of this analyzer is reported to be 94% for full morphological analyses, and 98%-99% when part-of-speech tag accuracy is not included.

An example of such a property is the distribution of part-of-speech bigrams.

Hana et al., (2004) demonstrate that adding such statistics from an annotated Czech corpus improves the performance of a Russian part-of-speech tagger over a fully unsupervised version.

pendent part-of-speech .

All features are conjoined with the part-of-speech tags of the words involved in the dependency to allow the guided parser to learn weights relative to different surface syntactic environments.

Unlike MSTParser, features are not explicitly defined to conjoin guide features with part-of-speech features.