Introduction
Indian Language Part-of-Speech Tagset: Sanskrit, Linguistic Data
Consortium (LDC) catalog number LDC2011T04 and isbn 1-58563-575-8, is
a corpus developed by Microsoft Research (MSR) India to support
the task of Part-of-Speech Tagging (POS) and other data-driven
linguistic research on Indian Languages in general. It is created as
a part of the
Indian
Language Part-of-Speech Tagset (IL-POST) project, a collaborative
effort among linguists and computer scientists from
MSR India, AU-KBC (Anna University,
Chennai), Delhi University, IIT Bombay, Jawaharlal Nehru University
(Delhi) and Tamil University (Tamilnadu).
The goal of the IL-POST project is to provide a common tagset
framework for Indian Languages that offers flexibility,
cross-linguistic compatibility and resuability across those
languages. It supports a three-level hierarchy of Categories, Types
and Attributes. The corpus mainly consists therefore of two different
levels of information for each lexical token: (a) lexical Category
and Types, and (b) set morphological attributes and their associated
values in the context.
Sanskrit is the classical language of Indian and the oldest documented language
of the Indo-European language family. It is also the liturgical language of
Hinduism, Buddhism and Jainism and one of the twenty-two official languages
of India. The name Sanskrit means refined, consecrated
and sanctified.
Data
This corpus contains 3,703 sentences (57,218
words) of manually annotated Sanskrit text selected from the Panchatrantra
stories, a collection of animal fables in verse and prose dating from the third
century BCE.
All annotated data is provided in both xml
and text files. The xml files are contained in the XML_files folder
and the text files in the text_files folder. Each data file contains
between 12,000-45,000 words. The XML file contains metadata about the material,
such as language, encoding and data size.
Annotation Procedure
The paper, Annotating Sanskrit
corpus: adapting IL-POSTS included in this release, contains a detailed
description of the annotation methodology.
Sample

Updates
Additional information, updates, bug fixes may be available in the
LDC catalog entry for this corpus at
LDC2011T04.
Content Copyright
Portions © 2010 Microsoft Research Labs India, Pvt. Ltd., © 2011
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