Papers by Paul Rayson
Towards a Welsh Semantic Annotation System (L18-1)
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| Challenge: | Automatic semantic annotation of natural language data is an important task in Natural Language Processing. |
| Approach: | They develop a Welsh semantic annotation tool that can be used to analyze Welsh text . it uses Lancaster's USAS semantic classification scheme to tag words with semantic tags . |
| Outcome: | The proposed tool can cover up to 91.78% of words in Welsh text. |
MasakhaNER: Named Entity Recognition for African Languages (2021.tacl-1)
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David Ifeoluwa Adelani, Jade Abbott, Graham Neubig, Daniel D’souza, Julia Kreutzer, Constantine Lignos, Chester Palen-Michel, Happy Buzaaba, Shruti Rijhwani, Sebastian Ruder, Stephen Mayhew, Israel Abebe Azime, Shamsuddeen H. Muhammad, Chris Chinenye Emezue, Joyce Nakatumba-Nabende, Perez Ogayo, Aremu Anuoluwapo, Catherine Gitau, Derguene Mbaye, Jesujoba Alabi, Seid Muhie Yimam, Tajuddeen Rabiu Gwadabe, Ignatius Ezeani, Rubungo Andre Niyongabo, Jonathan Mukiibi, Verrah Otiende, Iroro Orife, Davis David, Samba Ngom, Tosin Adewumi, Paul Rayson, Mofetoluwa Adeyemi, Gerald Muriuki, Emmanuel Anebi, Chiamaka Chukwuneke, Nkiruka Odu, Eric Peter Wairagala, Samuel Oyerinde, Clemencia Siro, Tobius Saul Bateesa, Temilola Oloyede, Yvonne Wambui, Victor Akinode, Deborah Nabagereka, Maurice Katusiime, Ayodele Awokoya, Mouhamadane MBOUP, Dibora Gebreyohannes, Henok Tilaye, Kelechi Nwaike, Degaga Wolde, Abdoulaye Faye, Blessing Sibanda, Orevaoghene Ahia, Bonaventure F. P. Dossou, Kelechi Ogueji, Thierno Ibrahima DIOP, Abdoulaye Diallo, Adewale Akinfaderin, Tendai Marengereke, Salomey Osei
| Challenge: | (2020) African languages are underrepresented in existing natural language processing datasets, research, and tools due to lack of datasets and reproducible results. |
| Approach: | They propose to create a dataset for named entity recognition (NER) in ten African languages. |
| Outcome: | The results of the first large dataset for named entity recognition (NER) in ten African languages are released to inform future research on African NLP. |
The IgboAPI Dataset: Empowering Igbo Language Technologies through Multi-dialectal Enrichment (2024.lrec-main)
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Chris Chinenye Emezue, Ifeoma Okoh, Chinedu Emmanuel Mbonu, Chiamaka Chukwuneke, Daisy Monika Lal, Ignatius Ezeani, Paul Rayson, Ijemma Onwuzulike, Chukwuma Onyebuchi Okeke, Gerald Okey Nweya, Bright Ikechukwu Ogbonna, Chukwuebuka Uchenna Oraegbunam, Esther Chidinma Awo-Ndubuisi, Akudo Amarachukwu Osuagwu
| Challenge: | UNESCO projects that the Igbo language will be endangered by 2025 . primary obstacle in developing dialectal-aware language technologies is lack of comprehensive dialectal datasets. |
| Approach: | They propose to use a multi-dialectal Igbo-English dictionary dataset to enhance the representation of Igbe dialects. |
| Outcome: | The proposed dataset enables machine translation systems to handle dialect variations in sentences. |
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms (P19-1)
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| Challenge: | evaluating models is a non-trivial task and requires extensive data and data splits to produce reliable comparisons. |
| Approach: | They propose a model selection approach that reduces the computational resources required to compare models based on single choices of random seeds. |
| Outcome: | The proposed model selection approach reduces the computational resources required to identify state-of-the-art models from large datasets. |
Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models (C18-1)
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| Challenge: | a recent study shows that performance estimations are unstable and variable . this makes it difficult to use parameter tuning and model selection . |
| Approach: | They propose to use a less variable CV method to evaluate performance . they propose lower choices of K than are typically seen in the NLP literature . |
| Outcome: | The proposed method can be used for parameter tuning and performance estimation, but it is unstable and unstable. |
Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for Target Dependent Sentiment Analysis (C18-1)
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| Challenge: | a lack of reproducibility and generalisability is a major threat to scientific development in Natural Language Processing. |
| Approach: | They propose to use a model zoo to document and release language models and published code . they recommend that future replication experiments should consider a variety of datasets . |
| Outcome: | The proposed methods are compared on six English datasets and are based on the results. |
Sinhala Encoder-only Language Models and Evaluation (2025.acl-long)
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Tharindu Ranasinghe, Hansi Hettiarachchi, Nadeesha Chathurangi Naradde Vidana Pathirana, Damith Premasiri, Lasitha Uyangodage, Isuri Nanomi Arachchige, Alistair Plum, Paul Rayson, Ruslan Mitkov
| Challenge: | Recent advances in language models (LMs) have produced excellent results in many NLP tasks, but their effectiveness is highly dependent on available pre-training resources. |
| Approach: | They propose to collect the largest monolingual corpus for Sinhala and compile a benchmark and evaluate LMs on it. |
| Outcome: | The proposed language models outperform the popular multilingual LMs in downstream NLP tasks. |
Profiling Medical Journal Articles Using a Gene Ontology Semantic Tagger (L18-1)
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| Challenge: | a growing number of scientific publications are based on sub-divisions and sub-communities of expertise becoming disconnected from each other. |
| Approach: | They propose to examine corpora derived from bodies of genetics literature and use it to make comparisons and improve retrieval methods. |
| Outcome: | The proposed methods will help to make comparisons and improve retrieval methods using domain knowledge via an existing gene ontology. |
Infrastructure for Semantic Annotation in the Genomics Domain (2020.lrec-1)
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Mahmoud El-Haj, Nathan Rutherford, Matthew Coole, Ignatius Ezeani, Sheryl Prentice, Nancy Ide, Jo Knight, Scott Piao, John Mariani, Paul Rayson, Keith Suderman
| Challenge: | a novel infrastructure for biomedical text mining combines NLP and corpus linguistics methods to provide a comprehensive corpus for literature-based discovery. |
| Approach: | They propose a novel pipeline for the collection, annotation, storage, retrieval and analysis of biomedical and life sciences literature . it uses an updatable Gene Ontology Semantic Tagger and a NLP pipeline scheduler to collect and process the corpus. |
| Outcome: | The proposed infrastructure allows for extreme-scale research on the open access PubMed Central archive. |
IgboBERT Models: Building and Training Transformer Models for the Igbo Language (2022.lrec-1)
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| Challenge: | This paper focuses on building resources for named entity recognition for Igbo, a language mainly spoken in the south eastern part of Nigeria. |
| Approach: | They present a standard Igbo named entity recognition dataset and results from fine-tuning transformer IgbeNER models. |
| Outcome: | The proposed dataset and model improves on the IgboNER task while training and fine-tuning a transformer model with comparatively little Igbe text data. |
Developing an Arabic Infectious Disease Ontology to Include Non-Standard Terminology (2020.lrec-1)
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| Challenge: | Existing ontologies for Arabic are difficult due to the lack of resources and the nature of the Arabic language. |
| Approach: | They propose to build an Arabic ontology that integrates scientific vocabularies with informal equivalents. |
| Outcome: | The proposed ontology integrates scientific vocabularies with informal equivalents in Arabic . it will be automatically generated but the results will be evaluated by a domain expert . |
LENS: Learning Entities from Narratives of Skin Cancer (2025.coling-demos)
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| Challenge: | Learning entities from narratives of skin cancer (LENS) is an automatic entity recognition system built on colloquial writings from skin cancer-related forums. |
| Approach: | They propose to use reddit forums to create an automatic entity recognition system that can be used to predict skin cancer outcomes. |
| Outcome: | LENS achieves an overall entity-level F1 score of 0.561 . other notable results include “CANC_T” (0.747), “STG” (0.888), “POB” (0.914), “GENDER” (0.750), “A/G” (00.646), “EMO” (0.619), and “MHD” (0.503). |
LexiDB: Patterns & Methods for Corpus Linguistic Database Management (2020.lrec-1)
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| Challenge: | LexiDB is a tool for storing, managing and querying corpus data. |
| Approach: | They propose to use LexiDB for storing, managing and querying corpus data. |
| Outcome: | The proposed methods outperform existing tools for corpus queries and storage. |
CoFiF Plus: A French Financial Narrative Summarisation Corpus (2022.lrec-1)
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| Challenge: | Existing corpora for financial narrative summarisation exists in English but there is a significant lack of financial text resources in the French language. |
| Approach: | They propose to use natural language processing to analyse financial documents to find the best summarisation methods. |
| Outcome: | The proposed dataset is the first to provide a comprehensive set of financial text written in French. |
Arabic Dialect Identification in the Context of Bivalency and Code-Switching (L18-1)
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| Challenge: | Existing methods for identifying Arabic dialects require significant amounts of annotated training data which is costly and time consuming to produce. |
| Approach: | They propose a novel approach to Arabic dialect identification using language bivalency and written code-switching to identify Arabic dialects. |
| Outcome: | The proposed method can reach more than 76% and score well (66%) when tested on unseen data. |