Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting

Gathika Ratnayaka; Nisansa De Silva; Amal Shehan Perera; Ramesh Pathirana

Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting

Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, Ramesh Pathirana

Correct Metadata for

Important: The Anthology treat PDFs as authoritative. Please use this form only to correct data that is out of line with the PDF. See our corrections guidelines if you need to change the PDF.

Title Adjust the title. Retain tags such as <fixed-case>.

Authors Adjust author names and order to match the PDF.

Abstract Correct abstract if needed. Retain XML formatting tags such as <tex-math>.

Verification against PDF Ensure that the new title/authors match the snapshot below. (If there is no snapshot or it is too small, consult the PDF.)

Authors concatenated from the text boxes above:

ALL author names match the snapshot above—including middle initials, hyphens, and accents.

Anthology ID:: 2020.paclic-1.29
Volume:: Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation
Month:: October
Year:: 2020
Address:: Hanoi, Vietnam
Editors:: Minh Le Nguyen, Mai Chi Luong, Sanghoun Song
Venue:: PACLIC
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 252–260
Language:
URL:: https://aclanthology.org/2020.paclic-1.29/
DOI:
Bibkey:
Cite (ACL):: Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, and Ramesh Pathirana. 2020. Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting. In Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pages 252–260, Hanoi, Vietnam. Association for Computational Linguistics.
Cite (Informal):: Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting (Ratnayaka et al., PACLIC 2020)
Copy Citation:
PDF:: https://aclanthology.org/2020.paclic-1.29.pdf
Data: SST, SST-5

PDF Cite Search Fix data

Export citation

BibTeX
MODS XML
Endnote
Preformatted

@inproceedings{ratnayaka-etal-2020-effective,
    title = "Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting",
    author = "Ratnayaka, Gathika  and
      de Silva, Nisansa  and
      Perera, Amal Shehan  and
      Pathirana, Ramesh",
    editor = "Nguyen, Minh Le  and
      Luong, Mai Chi  and
      Song, Sanghoun",
    booktitle = "Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation",
    month = oct,
    year = "2020",
    address = "Hanoi, Vietnam",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2020.paclic-1.29/",
    pages = "252--260"
}

Download as File

<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="ratnayaka-etal-2020-effective">
    <titleInfo>
        <title>Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Gathika</namePart>
        <namePart type="family">Ratnayaka</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Nisansa</namePart>
        <namePart type="family">de Silva</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Amal</namePart>
        <namePart type="given">Shehan</namePart>
        <namePart type="family">Perera</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Ramesh</namePart>
        <namePart type="family">Pathirana</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2020-10</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Minh</namePart>
            <namePart type="given">Le</namePart>
            <namePart type="family">Nguyen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Mai</namePart>
            <namePart type="given">Chi</namePart>
            <namePart type="family">Luong</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Sanghoun</namePart>
            <namePart type="family">Song</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Hanoi, Vietnam</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <identifier type="citekey">ratnayaka-etal-2020-effective</identifier>
    <location>
        <url>https://aclanthology.org/2020.paclic-1.29/</url>
    </location>
    <part>
        <date>2020-10</date>
        <extent unit="page">
            <start>252</start>
            <end>260</end>
        </extent>
    </part>
</mods>
</modsCollection>

Download as File

%0 Conference Proceedings
%T Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting
%A Ratnayaka, Gathika
%A de Silva, Nisansa
%A Perera, Amal Shehan
%A Pathirana, Ramesh
%Y Nguyen, Minh Le
%Y Luong, Mai Chi
%Y Song, Sanghoun
%S Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation
%D 2020
%8 October
%I Association for Computational Linguistics
%C Hanoi, Vietnam
%F ratnayaka-etal-2020-effective
%U https://aclanthology.org/2020.paclic-1.29/
%P 252-260

Download as File

Markdown (Informal)

[Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting](https://aclanthology.org/2020.paclic-1.29/) (Ratnayaka et al., PACLIC 2020)

Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting (Ratnayaka et al., PACLIC 2020)

ACL

Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, and Ramesh Pathirana. 2020. Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting. In Proceedings of the 34th Pacific Asia Conference on Language, Information and Computation, pages 252–260, Hanoi, Vietnam. Association for Computational Linguistics.