Arabic Summarizer

This tool provides an Arabic text summarizer that condenses long Arabic passages into concise, fluent summaries in Arabic. It supports articles, reports, transcripts, and notes, delivering outputs that preserve core ideas and named entities.
Conceptually, the process follows Arabic-aware preprocessing, sentence segmentation, and a controlled abstractive or extractive strategy. It normalizes orthography, tokenizes words, detects headings, and uses a graph-based ranking or neural scoring to select sentences. The summary length is controlled by a user-specified level (short, medium, long) and is post-processed for fluency and coherence. Named entities such as people and organizations are preserved or aligned to ensure traceability in the summary.
Beneficiaries include students needing quick study briefs, researchers scanning literature, journalists drafting briefs of articles, and content teams summarizing lengthy reports. Unique value comes from Arabic-specific handling: dialect-agnostic normalization, diacritic-aware segmentation, and retention of key terms in transliterated or script forms. Core features include language-aware normalization, length control, entity preservation, and API-friendly text output suitable for downstream NLP workflows.
Use cases include summarizing academic papers, policy documents, interviews, or social media threads in Arabic. The tool works as a standalone web service or integrated into data pipelines. It avoids translation, maintains Arabic syntax and style, and outputs a single summary in Arabic aligned to the selected length.
Compared to generic summarizers, this tool emphasizes Arabic linguistics, supports Modern Standard Arabic and narrow dialects, and provides deterministic results with configurable quality controls.