cs.CLOct 12, 2026

From Conceptual EneMonIE to an Executable Backend: A Modular Architecture for Energy Information Extractionand Grounded Question Answering

Authors: Janik Lesage, Khadim Lô, and Jean-Sébastien Dessureault

Organizations: Département de mathématiques et d’informatique, Université du Québec à Trois-Rivières, Canada

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Abstract

The original EneMonIE proposal describes a Web-based semantic system for continuously monitoring energy trends through targeted information extraction from heterogeneous online media. This article presents EneMonIE-Backend, an implementation-derived redesign that converts that conceptual pipeline into a modular, executable, and application-independent backend. The architecture separates five concerns: data sources, acquisition and normalization, semantic processing, knowledge organization, and persistent storage. It operationalizes configurable connectors for RSS feeds, URL collections, arXiv, social-media JSON files, and open-data CSV files; it also introduces question-driven Web search and scraping. Relevant documents pass through energy categorization, named entity recognition, temporal and event extraction, source sensitive sentiment analysis, and extractive summarization. The resulting semantic representations support entity co-occurrence graphs, cross-document interlinking, cluster-level information fusion, and relational persistence in SQLite. Three grounded question-answering paths are exposed at the backend level: live Web evidence, the stored corpus, and selected configured resources. Answer generation uses a language model when configured and otherwise falls back to deterministic extractive output. Unlike the original proposal, the presented architecture deliberately excludes the user-interface and server-side application layers, allowing the semantic core to be embedded in different applications. A deterministic smoke validation confirms relevance filtering, persistence, clustering, evidence retrieval, and document deletion. The work provides a reproducible architectural basis for future evaluation on larger multilingual energy corpora.

Figures & tables

Figure 1: Implementation-derived architecture of EneMonIE-Backend. The architecture is conceptually adapted and substantially extended from the original EneMonIE proposal by Küçük (2022) .
TablePurpose
documentsSource content, metadata, category, sentiment, and summary.
entitiesSurface forms, labels, canonical forms, and character spans.
temporalsTemporal mentions, normalized values, and spans.
eventsEvent types, triggers, sentences, times, and confidence.
entity_edgesWeighted co-occurrence relationships.
clustersFused titles, summaries, confidence, entities, and event types.
Table 1: Persistent data model.
ConcernOriginal EneMonIE proposalImplementation-derived architecture
SourcesNews, videos, social media, scholarly articles, organizational sites, and open data.Concrete adapters for RSS, URL lists, arXiv, JSONL, and CSV, plus question-driven Web search and scraping.
FilteringOntology-based text categorization.Weighted keyword scoring with a configurable relevance threshold before downstream processing.
Information extractionNER, temporal expressions, and energy-event extraction.Explicit rule- and gazetteer-based modules returning typed objects with spans, canonical values, times, and confidence.
SentimentOpinion analysis for social-media text.Source-sensitive English/French lexicon analysis applied only to social-media documents.
Interlinking and fusionAlign related media, fuse information, and summarize it.Weighted Jaccard similarity, threshold graph, connected-component clusters, mean-similarity confidence, and extractive fusion.
Knowledge structureSocial-network construction and a central relational database.Entity co-occurrence edges and a seven-table SQLite schema with foreign keys and cascade deletion.
Table 2: Relationship between the original proposal and the implementation-derived architecture.
TaskNNPRF1F_{1}
Entities100.5881.0000.741
Events71.0001.0001.000
Temporal spans51.0001.0001.000
Table 3: Extraction results on seven recovered synthetic documents.
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