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Mehwish Alam

Mehwish Alam has 3 papers in our library, in 2022–2026, most of them on Named entity recognition, Multilingual & cross-lingual NLP, Semitic languages; often with Cristian Santini, Fouad Shammary, Haithem Afli.

3 papers in our library · 2022–2026

OpenAlex · ORCID · Wikidata · h-index 13 · 209 works · 720 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 15 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10108

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 12 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. TF-IDF or Transformers for Arabic Dialect Identification? ITFLOWS participation in the NADI 2022 Shared Task (2022 · 7 citations)
    The paper describes the ITFLOWS team's entry to NADI 2022 Subtask 1, which asks systems to label tweets with the country-level Arabic dialect they come from.
  2. It's All About the Confidence: An Unsupervised Approach for Multilingual Historical Entity Linking using Large Language Models (2026 · 1 citation)
    The paper tackles entity linking on historical documents, where OCR noise, language variation, multilinguality and many entities absent from knowledge bases (NIL entities) degrade standard systems.
  3. ENEIDE: A High Quality Silver Standard Dataset for Named Entity Recognition and Linking in Historical Italian (2026)
    Historical Italian has very few annotated resources for Named Entity Recognition and Linking (NERL). The only earlier dataset, MHERCL, covers just music periodicals and offers only a test split, so it cannot be used for training. ENEIDE fills this gap by converting expert entity markup from two Scholarly Digital…

All works

4 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. YAGO 4.5: A Large and Clean Knowledge Base with a Rich Taxonomy ↗arXiv:2308.11884 · no summary yetFabian Suchanek et al.2023 · 49 citations

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 15 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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