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Found 36 papers, 11 papers with code
MasakhaNER: Named Entity Recognition for African Languages
We take a step towards addressing the under-representation of the African continent in NLP research by creating the first large publicly available high-quality dataset for named entity recognition (NER) in ten African languages, bringing together a variety of stakeholders.
Lexical Coverage Evaluation of Large-scale Multilingual Semantic Lexicons for Twelve Languages
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.
BOSS: Bayesian Optimization over String Spaces
This article develops a Bayesian optimization (BO) method which acts directly over raw strings, proposing the first uses of string kernels and genetic algorithms within BO loops.
Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for Target Dependent Sentiment Analysis
Lack of repeatability and generalisability are two significant threats to continuing scientific development in Natural Language Processing.
Lancaster A at SemEval-2017 Task 5: Evaluation metrics matter: predicting sentiment from financial news headlines
This paper describes our participation in Task 5 track 2 of SemEval 2017 to predict the sentiment of financial news headlines for a specific company on a continuous scale between -1 and 1.
FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms
We present FIESTA, a model selection approach that significantly reduces the computational resources required to reliably identify state-of-the-art performance from large collections of candidate models.
Using J-K fold Cross Validation to Reduce Variance When Tuning NLP Models
K-fold cross validation (CV) is a popular method for estimating the true performance of machine learning models, allowing model selection and parameter tuning.
Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models
K-fold cross validation (CV) is a popular method for estimating the true performance of machine learning models, allowing model selection and parameter tuning.
Understanding who uses Reddit: Profiling individuals with a self-reported bipolar disorder diagnosis
Recently, research on mental health conditions using public online data, including Reddit, has surged in NLP and health research but has not reported user characteristics, which are important to judge generalisability of findings.
Creating and Validating Multilingual Semantic Representations for Six Languages: Expert versus Non-Expert Crowds
Creating high-quality wide-coverage multilingual semantic lexicons to support knowledge-based approaches is a challenging time-consuming manual task.
Detecting Document Structure in a Very Large Corpus of UK Financial Reports
In this paper we present the evaluation of our automatic methods for detecting and extracting document structure in annual financial reports.
Experiences with Parallelisation of an Existing NLP Pipeline: Tagging Hansard
This is contrasted with a description of the cluster on which it was to run, and specific limitations are discussed such as the overhead of using SAN-based storage.
Document Attrition in Web Corpora: an Exploration
Increases in the use of web data for corpus-building, coupled with the use of specialist, single-use corpora, make for an increasing reliance on language that changes quickly, affecting the long-term validity of studies based on these methods.
In Search of Meaning: Lessons, Resources and Next Steps for Computational Analysis of Financial Discourse
We critically assess mainstream accounting and finance research applying methods from computational linguistics (CL) to study financial discourse.
OSMAN ― A Novel Arabic Readability Metric
The Arabic sentences were written with the absence of diacritics and in order to count the number of syllables we added the diacritics in using an open source tool called Mishkal.
Learning Tone and Attribution for Financial Text Mining
Previous studies have only applied manual content analysis on a small scale to reveal such a bias in the narrative section of annual financial reports.
UPPC - Urdu Paraphrase Plagiarism Corpus
Paraphrase plagiarism is a significant and widespread problem and research shows that it is hard to detect.
Leveraging Pre-Trained Embeddings for Welsh Taggers
While the application of word embedding models to downstream Natural Language Processing (NLP) tasks has been shown to be successful, the benefits for low-resource languages is somewhat limited due to lack of adequate data for training the models.
Igbo-English Machine Translation: An Evaluation Benchmark
Although researchers and practitioners are pushing the boundaries and enhancing the capacities of NLP tools and methods, works on African languages are lagging.
Unfinished Business: Construction and Maintenance of a Semantically Tagged Historical Parliamentary Corpus, UK Hansard from 1803 to the present day
Creating, curating and maintaining modern political corpora is becoming an ever more involved task.
LexiDB: Patterns \& Methods for Corpus Linguistic Database Management
LexiDB is a tool for storing, managing and querying corpus data.
Developing an Arabic Infectious Disease Ontology to Include Non-Standard Terminology
Building ontologies is a crucial part of the semantic web endeavour.
Infrastructure for Semantic Annotation in the Genomics Domain
The corpus database is distributed to permit fast indexing, and provides a simple web front-end with corpus linguistics methods for sub-corpus comparison and retrieval.
MUMBO: MUlti-task Max-value Bayesian Optimization
MUMBO is scalable and efficient, allowing multi-task Bayesian optimization to be deployed in problems with rich parameter and fidelity spaces.
BOSH: Bayesian Optimization by Sampling Hierarchically
Deployments of Bayesian Optimization (BO) for functions with stochastic evaluations, such as parameter tuning via cross validation and simulation optimization, typically optimize an average of a fixed set of noisy realizations of the objective function.
The National Corpus of Contemporary Welsh: Project Report | Y Corpws Cenedlaethol Cymraeg Cyfoes: Adroddiad y Prosiect
This report provides an overview of the CorCenCC project and the online corpus resource that was developed as a result of work on the project.
COVID-19 and Arabic Twitter: How can Arab World Governments and Public Health Organizations Learn from Social Media?
We find that Machine Learning classifiers are able to correctly identify the rumour related tweets with 84{\%} accuracy.
GIBBON: General-purpose Information-Based Bayesian OptimisatioN
This paper describes a general-purpose extension of max-value entropy search, a popular approach for Bayesian Optimisation (BO).
IgboBERT Models: Building and Training Transformer Models for the Igbo Language
Our results show that, although the IgboNER task benefited hugely from fine-tuning large transformer model, fine-tuning a transformer model built from scratch with comparatively little Igbo text data seems to yield quite decent results for the IgboNER task.
AraSAS: The Open Source Arabic Semantic Tagger
This paper presents (AraSAS) the first open-source Arabic semantic analysis tagging system.
