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        <title>‘ChemXtract’ A System for Extraction of Chemical Events from Patent Documents</title>
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    <name type="personal">
        <namePart type="given">Pattabhi</namePart>
        <namePart type="family">RK Rao</namePart>
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            <title>Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing</title>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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            <namePart type="family">Angelova</namePart>
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            <publisher>INCOMA Ltd., Shoumen, Bulgaria</publisher>
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    <abstract>ChemXtraxt main goal is to extract the chemical events from patent documents. Event extraction requires that we first identify the names of chemical compounds involved in the events. Thus, in this work two extractions are done and they are (a) names of chemical compounds and (b) event that identify the specific involvement of the chemical compounds in a chemical reaction. Extraction of essential elements of a chemical reaction, generally known as Named Entity Recognition (NER), extracts the compounds, condition and yields, their specific role in reaction and assigns a label according to the role it plays within a chemical reaction. Whereas event extraction identifies the chemical event relations between the chemical compounds identified. Here in this work we have used Neural Conditional Random Fields (NCRF), which combines the power of artificial neural network (ANN) and CRFs. Different levels of features that include linguistic, orthographical and lexical clues are used. The results obtained are encouraging.</abstract>
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        <url>https://aclanthology.org/2023.ranlp-1.106</url>
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        <date>2023-09</date>
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%0 Conference Proceedings
%T ‘ChemXtract’ A System for Extraction of Chemical Events from Patent Documents
%A RK Rao, Pattabhi
%A Lalitha Devi, Sobha
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F rk-rao-lalitha-devi-2023-chemxtract
%X ChemXtraxt main goal is to extract the chemical events from patent documents. Event extraction requires that we first identify the names of chemical compounds involved in the events. Thus, in this work two extractions are done and they are (a) names of chemical compounds and (b) event that identify the specific involvement of the chemical compounds in a chemical reaction. Extraction of essential elements of a chemical reaction, generally known as Named Entity Recognition (NER), extracts the compounds, condition and yields, their specific role in reaction and assigns a label according to the role it plays within a chemical reaction. Whereas event extraction identifies the chemical event relations between the chemical compounds identified. Here in this work we have used Neural Conditional Random Fields (NCRF), which combines the power of artificial neural network (ANN) and CRFs. Different levels of features that include linguistic, orthographical and lexical clues are used. The results obtained are encouraging.
%U https://aclanthology.org/2023.ranlp-1.106
%P 988-995

Markdown (Informal)

[‘ChemXtract’ A System for Extraction of Chemical Events from Patent Documents](https://aclanthology.org/2023.ranlp-1.106) (RK Rao & Lalitha Devi, RANLP 2023)

• ‘ChemXtract’ A System for Extraction of Chemical Events from Patent Documents (RK Rao & Lalitha Devi, RANLP 2023)

ACL

• Pattabhi RK Rao and Sobha Lalitha Devi. 2023. ‘ChemXtract’ A System for Extraction of Chemical Events from Patent Documents. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 988–995, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.