<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="tanev-2022-ontopopulis">
    <titleInfo>
        <title>OntoPopulis, a System for Learning Semantic Classes</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Hristo</namePart>
        <namePart type="family">Tanev</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2022-09</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 5th International Conference on Computational Linguistics in Bulgaria (CLIB 2022)</title>
        </titleInfo>
        <originInfo>
            <publisher>Department of Computational Linguistics, IBL – BAS</publisher>
            <place>
                <placeTerm type="text">Sofia, Bulgaria</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>Ontopopulis is a multilingual weakly supervised terminology learning algorithm which takes on its input a set of seed terms for a semantic category and an unannotated text corpus. The algorithm learns additional terms, which belong to this category. For example, for the category “environmental disasters” the input seed set in English is environmental disaster, water pollution, climate change. Among the highest ranked new terms which the system learns for this semantic class are deforestation, global warming and so on.</abstract>
    <identifier type="citekey">tanev-2022-ontopopulis</identifier>
    <location>
        <url>https://aclanthology.org/2022.clib-1.1</url>
    </location>
    <part>
        <date>2022-09</date>
        <extent unit="page">
            <start>8</start>
            <end>12</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T OntoPopulis, a System for Learning Semantic Classes
%A Tanev, Hristo
%S Proceedings of the 5th International Conference on Computational Linguistics in Bulgaria (CLIB 2022)
%D 2022
%8 September
%I Department of Computational Linguistics, IBL – BAS
%C Sofia, Bulgaria
%F tanev-2022-ontopopulis
%X Ontopopulis is a multilingual weakly supervised terminology learning algorithm which takes on its input a set of seed terms for a semantic category and an unannotated text corpus. The algorithm learns additional terms, which belong to this category. For example, for the category “environmental disasters” the input seed set in English is environmental disaster, water pollution, climate change. Among the highest ranked new terms which the system learns for this semantic class are deforestation, global warming and so on.
%U https://aclanthology.org/2022.clib-1.1
%P 8-12

Markdown (Informal)

[OntoPopulis, a System for Learning Semantic Classes](https://aclanthology.org/2022.clib-1.1) (Tanev, CLIB 2022)

• OntoPopulis, a System for Learning Semantic Classes (Tanev, CLIB 2022)

ACL

• Hristo Tanev. 2022. OntoPopulis, a System for Learning Semantic Classes. In Proceedings of the 5th International Conference on Computational Linguistics in Bulgaria (CLIB 2022), pages 8–12, Sofia, Bulgaria. Department of Computational Linguistics, IBL -- BAS.