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SHR++: An Interface for Morpho-syntactic annotation of Sanskrit Corpora

  • Amrith Krishna
    ,
  • Shiv Vidhyut
    ,
  • Dilpreet Chawla
    ,
  • Sruti Sambhavi
    ,
  • Pawan Goyal
  • ,
  • ,
  • International Institute of Information Technology Bangalore
    ,
  • NIT - National Institute of Technology Rourkela
    ,
  • Indian Institute of Technology Kharagpur
Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Open access

Publication Information

Output type

Research Output:
Conference Article in Proceeding or Book/Report chapter
Article in proceedings
Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 7069–7076

Publication milestones

  • Published - 02/2020

Publication status

Published - 02/2020

Publisher

Association for Computational Linguistics, United States

Publication IDs

  • Scopus: 85096512176

Host publication title

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020),

Abstract

We propose a web-based annotation framework, SHR++, for morpho-syntactic annotation of corpora in Sanskrit. SHR++ is designed
to generate annotations for the word-segmentation, morphological parsing and dependency analysis tasks in Sanskrit. It incorporates
analyses and predictions from various tools designed for processing texts in Sanskrit, and utilises them to ease the cognitive load of
the human annotators. Specifically, SHR++ uses Sanskrit Heritage Reader (Goyal and Huet, 2016), a lexicon driven shallow parser
for enumerating all the phonetically and lexically valid word splits along with their morphological analyses for a given string. This
would help the annotators in choosing the solutions, rather than performing the segmentations by themselves. Further, predictions from
a word segmentation tool (Krishna et al., 2018) are added as suggestions that can aid the human annotators in their decision making.
Our evaluation shows that enabling this segmentation suggestion component reduces the annotation time by 20.15 %. SHR++ can
be accessed online at http://vidhyut97.pythonanywhere.com/ and the codebase, for the independent deployment of the system elsewhere, is hosted at https://github.com/iamdsc/smart-sanskrit-annotator.

Publication metrics

PlumX

Citations
5
Captures
66

Related Event

Title

Conference on Linguistic Resources and Evaluation

Event type

Conference

Degree of recognition

International event

Date

20/06/2022 - 25/06/2022

Location

Palais du PharoMarseilleFrance