<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="kharlashkin-etal-2025-oracle">
    <titleInfo>
        <title>ORACLE: Time-Dependent Recursive Summary Graphs for Foresight on News Data Using LLMs</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Lev</namePart>
        <namePart type="family">Kharlashkin</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Eiaki</namePart>
        <namePart type="given">V</namePart>
        <namePart type="family">Morooka</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Yehor</namePart>
        <namePart type="family">Tereschenko</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Mika</namePart>
        <namePart type="family">Hämäläinen</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2025-12</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 10th International Workshop on Computational Linguistics for Uralic Languages</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Mika</namePart>
            <namePart type="family">Hämäläinen</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Michael</namePart>
            <namePart type="family">Rießler</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Eiaki</namePart>
            <namePart type="given">V</namePart>
            <namePart type="family">Morooka</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Lev</namePart>
            <namePart type="family">Kharlashkin</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Joensuu, Finland</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
        <identifier type="isbn">979-8-89176-360-9</identifier>
    </relatedItem>
    <abstract>ORACLE turns daily news into week-over-week, decision-ready insights for one of the Finnish University of Applied Sciences. The platform crawls and versions news, applies University-specific relevance filtering, embeds content, classifies items into PESTEL dimensions and builds a concise Time-Dependent Recursive Summary Graph (TRSG): two clustering layers summarized by an LLM and recomputed weekly. A lightweight change detector highlights what is new, removed or changed, then groups differences into themes for PESTEL-aware analysis. We detail the pipeline, discuss concrete design choices that make the system stable in production and present a curriculum-intelligence use case with an evaluation plan.</abstract>
    <identifier type="citekey">kharlashkin-etal-2025-oracle</identifier>
    <location>
        <url>https://aclanthology.org/2025.iwclul-1.10/</url>
    </location>
    <part>
        <date>2025-12</date>
        <extent unit="page">
            <start>72</start>
            <end>76</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T ORACLE: Time-Dependent Recursive Summary Graphs for Foresight on News Data Using LLMs
%A Kharlashkin, Lev
%A Morooka, Eiaki V.
%A Tereschenko, Yehor
%A Hämäläinen, Mika
%Y Hämäläinen, Mika
%Y Rießler, Michael
%Y Morooka, Eiaki V.
%Y Kharlashkin, Lev
%S Proceedings of the 10th International Workshop on Computational Linguistics for Uralic Languages
%D 2025
%8 December
%I Association for Computational Linguistics
%C Joensuu, Finland
%@ 979-8-89176-360-9
%F kharlashkin-etal-2025-oracle
%X ORACLE turns daily news into week-over-week, decision-ready insights for one of the Finnish University of Applied Sciences. The platform crawls and versions news, applies University-specific relevance filtering, embeds content, classifies items into PESTEL dimensions and builds a concise Time-Dependent Recursive Summary Graph (TRSG): two clustering layers summarized by an LLM and recomputed weekly. A lightweight change detector highlights what is new, removed or changed, then groups differences into themes for PESTEL-aware analysis. We detail the pipeline, discuss concrete design choices that make the system stable in production and present a curriculum-intelligence use case with an evaluation plan.
%U https://aclanthology.org/2025.iwclul-1.10/
%P 72-76

Markdown (Informal)

[ORACLE: Time-Dependent Recursive Summary Graphs for Foresight on News Data Using LLMs](https://aclanthology.org/2025.iwclul-1.10/) (Kharlashkin et al., IWCLUL 2025)

• ORACLE: Time-Dependent Recursive Summary Graphs for Foresight on News Data Using LLMs (Kharlashkin et al., IWCLUL 2025)

ACL

• Lev Kharlashkin, Eiaki V. Morooka, Yehor Tereschenko, and Mika Hämäläinen. 2025. ORACLE: Time-Dependent Recursive Summary Graphs for Foresight on News Data Using LLMs. In Proceedings of the 10th International Workshop on Computational Linguistics for Uralic Languages, pages 72–76, Joensuu, Finland. Association for Computational Linguistics.