Treebank Annotation

By –

Mohit Jasapara – 2012EEB1059

Aashish Kholiya – 2012MEB1083

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Treebank

The term treebank was coined by linguist Geoffrey Leech in the 1980s because both syntactic and semantic structure are commonly represented compositionally as a tree structure.

In linguistics , a treebank is a parsed text corpus that annotates syntactic or semantic sentence structure.

In simple words, treebanks are collections of manually checked syntactic analyses of sentences.

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Treebank3

Construction

Treebanks are often created on top of a corpus that has already been annotated with part-of-speech tags.

treebanks are sometimes enhanced with semantic or other linguistic information.

Treebanks can be created completely manually, where linguists annotate each sentence with syntactic structure, or semi-automatically, where a parser assigns some syntactic structure which linguists then check and, if necessary, correct

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Construction

In practice, fully checking and completing the parsing of natural language corpora is a labour-intensive project that can take teams of graduate linguists several years.

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.

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Construction

Some treebanks follow a specific linguistic theory in their syntactic annotation

(e.g. the BulTreeBank follows HPSG) but most try to be less theory-specific.

However, two main groups can be distinguished:

treebanks that annotate phrase structure (for example the Penn Treebank or ICE-GB) and

those that annotate dependency structure (for example the Prague Dependency Treebank or the Quranic Arabic Dependency Treebank).

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Construction

It is important to clarify the distinction between the formal representation and the file format used to store the annotated data.

Treebanks are necessarily constructed according to a particular grammar. The same grammar may be implemented by different file formats.

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Construction

For example, the syntactic analysis for John loves Mary, shown in the figure on the right, may be represented by simple labelled brackets in a text file, like this (following the Penn Treebank notation):

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Construction

This type of representation is popular because it is light on resources, and the tree structure is relatively easy to read without software tools. However as corpora become increasingly complex, other file formats may be preferred. Alternatives include treebank-specific XML schemes, numbered indentation and various types of standoff notation.

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Applications

Computational perspective

From a computational perspective, Treebank have been used to engineer state-of-the-art natural language processing systems such as part-of-speech taggers, parsers, semantic analyzers and machine translation systems.

Most computational systems utilize gold-standard Treebank data.

However, an automatically parsed corpus that is not corrected by human linguists can still be useful.

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Applications

It can provide evidence of rule frequency for a parser.

A parser may be improved by applying it to large amounts of text and gathering rule frequencies.

However, it should be obvious that only by a process of correcting and completing a corpus by hand is it possible then to identify rules absent from the parser knowledge base. In addition, frequencies are likely to be more accurate.

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Applications

Corpus linguistics

In corpus linguistics, Treebank are used to study syntactic phenomena

for example, diachronic corpora can be used to study the time course of syntactic change.

Once parsed, a corpus will contain frequency evidence showing how common different grammatical structures are in use.

Treebank also provide evidence of coverage and support the discovery of new, unanticipated, grammatical phenomena.

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Applications

Interaction research is particularly fruitful as further layers of annotation, e.g. semantic, pragmatic, are added to a corpus.

It is then possible to evaluate the impact of non-syntactic phenomena on grammatical choices

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Applications

Theoretical linguistics and Psycholinguistics

Another use of Treebank in theoretical linguistics and psycholinguistics is interaction evidence.

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, and to try to understand how speakers and writers make decisions as they form sentences.

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Penn Treebank Project

The Penn Treebank Project annotates naturally-occurring text for linguistic structure.

Most notably, it produces skeletal parses showing rough syntactic and semantic information -- a bank of linguistic trees.

It also annotate text with part-of-speech tags, and for the Switchboard corpus of telephone conversations, dysfluency annotation.

It is located in the LINC Laboratory of the Computer and Information Science Department at the University of Pennsylvania.

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Penn Treebank Project

The Linguistic Data Consortium(LDC) provides tools and formats for creating and managing linguistic annotations.

`Linguistic annotation‘ covers any descriptive or analytic notations applied to raw language data.

The Penn Treebank is a human-annotated and partially `skeletally' parsed corpus consisting of over 4.5 million words of American English.

It includes the Brown Corpus (retagged) and the Wall Street Journal Corpus, as well as Department of Energy abstracts, Dow Jones Newswire stories, Department of Agriculture bulletins, Library of America texts, MUC-3 messages, IBM Manual sentences, WBUR radio transcripts, and ATIS sentences.

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References

http://en.wikipedia.org/wiki/Treebank

http://www.cis.upenn.edu/~treebank/

https://catalog.ldc.upenn.edu/LDC97S62

http://mshang.ca/syntree/

http://faculty.washington.edu/fxia/LAWVI/workshop_presentation_slides/special_session/pml/

http://www.seas.upenn.edu/~pdtb/tools.shtml

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