Rao Muhammad Adeel Nawab


2016

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Urdu Summary Corpus
Muhammad Humayoun | Rao Muhammad Adeel Nawab | Muhammad Uzair | Saba Aslam | Omer Farzand
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Language resources, such as corpora, are important for various natural language processing tasks. Urdu has millions of speakers around the world but it is under-resourced in terms of standard evaluation resources. This paper reports the construction of a benchmark corpus for Urdu summaries (abstracts) to facilitate the development and evaluation of single document summarization systems for Urdu language. In Urdu, space does not always mark word boundary. Therefore, we created two versions of the same corpus. In the first version, words are separated by space. In contrast, proper word boundaries are manually tagged in the second version. We further apply normalization, part-of-speech tagging, morphological analysis, lemmatization, and stemming for the articles and their summaries in both versions. In order to apply these annotations, we re-implemented some NLP tools for Urdu. We provide Urdu Summary Corpus, all these annotations and the needed software tools (as open-source) for researchers to run experiments and to evaluate their work including but not limited to single-document summarization task.

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UPPC - Urdu Paraphrase Plagiarism Corpus
Muhammad Sharjeel | Paul Rayson | Rao Muhammad Adeel Nawab
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Paraphrase plagiarism is a significant and widespread problem and research shows that it is hard to detect. Several methods and automatic systems have been proposed to deal with it. However, evaluation and comparison of such solutions is not possible because of the unavailability of benchmark corpora with manual examples of paraphrase plagiarism. To deal with this issue, we present the novel development of a paraphrase plagiarism corpus containing simulated (manually created) examples in the Urdu language - a language widely spoken around the world. This resource is the first of its kind developed for the Urdu language and we believe that it will be a valuable contribution to the evaluation of paraphrase plagiarism detection systems.

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Lexical Coverage Evaluation of Large-scale Multilingual Semantic Lexicons for Twelve Languages
Scott Piao | Paul Rayson | Dawn Archer | Francesca Bianchi | Carmen Dayrell | Mahmoud El-Haj | Ricardo-María Jiménez | Dawn Knight | Michal Křen | Laura Löfberg | Rao Muhammad Adeel Nawab | Jawad Shafi | Phoey Lee Teh | Olga Mudraya
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

The last two decades have seen the development of various semantic lexical resources such as WordNet (Miller, 1995) and the USAS semantic lexicon (Rayson et al., 2004), which have played an important role in the areas of natural language processing and corpus-based studies. Recently, increasing efforts have been devoted to extending the semantic frameworks of existing lexical knowledge resources to cover more languages, such as EuroWordNet and Global WordNet. In this paper, we report on the construction of large-scale multilingual semantic lexicons for twelve languages, which employ the unified Lancaster semantic taxonomy and provide a multilingual lexical knowledge base for the automatic UCREL semantic annotation system (USAS). Our work contributes towards the goal of constructing larger-scale and higher-quality multilingual semantic lexical resources and developing corpus annotation tools based on them. Lexical coverage is an important factor concerning the quality of the lexicons and the performance of the corpus annotation tools, and in this experiment we focus on evaluating the lexical coverage achieved by the multilingual lexicons and semantic annotation tools based on them. Our evaluation shows that some semantic lexicons such as those for Finnish and Italian have achieved lexical coverage of over 90% while others need further expansion.

2012

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Natural Language Descriptions of Visual Scenes Corpus Generation and Analysis
Muhammad Usman Ghani Khan | Rao Muhammad Adeel Nawab | Yoshihiko Gotoh
Proceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)

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Detecting Text Reuse with Modified and Weighted N-grams
Rao Muhammad Adeel Nawab | Mark Stevenson | Paul Clough
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)