treebank

One of the key ways to extract evidence from a treebank is through search tools.

What is the purpose of a treebank?

One of the most cited English linguistic corpora is the Penn Treebank.

The specialisation uses the Explanation Based Learning algorithm to create a treebank from the training corpus.

An annotated treebank of Quranic Arabic.

Index Thomisticus Treebank.

This comparison uses the Penn tag set on some of the Penn Treebank data, so the results are directly comparable.

A syntactically annotated corpus (treebank) is a part of Russian National Corpus.

A completed treebank can help linguists carry out experiments as to how the decision to use one grammatical construction tends to influence the decision to form others.

See Part of speech tagging for more general information including descriptions of the Penn Treebank and other sets of tags.

In support of this view Sampson provides an analysis of over eight thousand parsed noun phrases from the LOB treebank.

A treebank or parsed corpus is a text corpus in which each sentence has been parsed, i.e. annotated with syntactic structure.

In 2006 the Index Thomisticus Treebank project (directed by Marco Passarotti) started the syntactic annotation of the entire corpus.

Prague Arabic Dependency Treebank (PADT)

PerTreeBank (HPSG-based Syntactic Treebank)

The level of annotation detail and the breadth of the linguistic sample determine the difficulty of the task and the length of time required to build a treebank.

Here a rich domain theory, i.e., a natural language grammar---although neither perfect nor complete, is tuned to a particular application or particular language usage, using a treebank (training examples).

The PropBank corpus added manually created semantic role annotations to the Penn TreeBank corpus of Wall Street Journal texts.

Verbmobil treebanks: Tübingen Treebank of Japanese / Spontaneous Speech (TüBa-J/S)

The treebank can be thoroughly searched and explored with the ICE Corpus Utility Program or ICECUP software.

Unlike other probabilistic models, DOP takes into account all subtrees contained in a treebank rather than being restricted to, for example, 2-level subtrees (like PCFGs).

The most popular "tag set" for POS tagging for American English is probably the Penn tag set, developed in the Penn Treebank project.

MontyTagger: Part-of-speech tagging using the Penn Treebank tagset, enriched with "Common Sense" from the Open Mind Common Sense project.

Persian Dependency Treebank (PerDT) (Dependency-based Syntactic Treebank)

Polish: A Treebank / Test Suite for Polish (HPSG treebank)