Results 71 to 80 of about 221,296 (163)

Corpus Bootstrapping for Syriac Linguistics

Journal of Open Humanities Data
The present article summarises a bootstrapping approach to Syriac corpus linguistics that gives freedom for Syriac researchers to apply part-of-speech (POS) tagging technology on texts of their choice using the SEDRA API mechanism and offers an annotated
Charbel El-Khaissi
doaj   +1 more source

Implementation of Conditional Random Fields Algorithm for Part of Speech Tagging in Madurese Language

JSiI (Jurnal Sistem Informasi)
Penelitian ini berfokus pada penerapan Conditional Random Fields (CRF) untuk Part of Speech (POS) Tagging dalam bahasa Madura. Mengingat keterbatasan sumber daya pemrosesan bahasa alami (NLP) untuk bahasa daerah, khususnya bahasa Madura, studi ini ...
Rizky Sulaiman, Setio Basuki
doaj   +3 more sources

On the development of a tagset for Northern Sotho with special reference to the issue of standardisation

Literator, 2008
Working with corpora in the South African Bantu languages has up till now been limited to the utilisation of raw corpora. Such corpora, however, have limited functionality.
E. Taljard, G. Faaß, U. Heid, D.J. Prinsloo   +3 more
doaj   +1 more source

BatteryDataExtractor: battery-aware text-mining software embedded with BERT models. [PDF]

Chem Sci, 2022
Huang S, Cole JM.
europepmc   +1 more source

Strategy for modular assembly of tetravalent, multispecific antibodies

Protein Science, Volume 35, Issue 10, October 2026.
Abstract Multispecific, multivalent antibodies (Abs) are a burgeoning class of drugs that dramatically expand the pharmacological repertoire beyond traditional therapeutic Abs. Here, we present a simple, modular approach to developing multispecific, multivalent Abs based on a Fab‐phage library with a single light chain.
Evan Mallette, Levi L. Blazer, Craig A. Hokanson, Chao Chen, Julia Garcia Perez, Alevtina Pavlenco, Lynda Ploder, Alexander U. Singer, Michael D. L. Suits, Sunil Bhakta, Jagath R. Junutula, Jarrett J. Adams, Sachdev S. Sidhu   +12 more
wiley   +1 more source

Chakma Language POS Tagging Dataset

, 2023
The Chakma Language POS Tagging Dataset is a valuable linguistic resource designed for the analysis and understanding of the Chakma language. Chakma is a member of the Indo-Aryan language family and is primarily spoken by the Chakma people in the ...
Rahman, Mushfiqur, Rahman, M (via Mendeley Data)   +1 more
core   +1 more source

Getting to the Core of the Matter—Assessing the Role of Replication in Metabarcoding‐Based sedaDNA

Molecular Ecology Resources, Volume 26, Issue 7, October 2026.
ABSTRACT Replication is central to most experimental and sampling designs, increasing inferential power and capturing fine‐scale data heterogeneity. However, its importance remains poorly evaluated in some ecological and evolutionary settings. This is the case of metabarcoding studies using DNA recovered from sedimentary archives, in which biological ...
Elena Baños, Clara Ras Segura, Erik J. De Boer, Andrew B. Cundy, Xavier Turon Barrera, Sandra Nogué, Luke E. Holman, Marc Rius   +7 more
wiley   +1 more source

A Hybrid Neural-CRF Framework for Assamese Part-of-Speech Tagging

IEEE Access
Natural Language Processing (NLP) involves computational techniques for analyzing and understanding human languages. Part-of-Speech (POS) tagging, a fundamental NLP task, assigns grammatical categories to words in text.
Rituraj Phukan, Nomi Baruah, Mandira Neog, Shikhar KR. Sarma, Darpanjit Konwar   +4 more
doaj   +1 more source

Genetic Mapping for Winter‐Hardiness in a Miscanthus sacchariflorus × M. sinensis (Hardy × Non‐Hardy) F2 Population

GCB Bioenergy, Volume 18, Issue 10, October 2026.
Genetic mapping of a Miscanthus sacchariflorus × M. sinensis F2 population identified 37 QTLs associated with winter‐hardiness, including repeated regions across traits and years. Favorable alleles from the hardy M. sacchariflorus parent and candidate cold‐stress genes highlight targets for marker‐assisted breeding of winter‐hardy biomass cultivars ...
Xuying Zheng, Nick Labonte, Hongxu Dong, Shailendra Sharma, Katarzyna Glowacka, Lindsay V. Clark, John A. Juvik, Dessireé Zerpa‐Catanho, Erik J. Sacks   +8 more
wiley   +1 more source

INVESTIGATING INTENSIFIER EFFECTS IN LOW-RESOURCE LANGUAGES USING CONVENTIONAL AND DEEP LEARNING MODELS [PDF]

ICTACT Journal on Soft Computing
In this study, two machine learning models, Long Short Term Memory (LSTM) and BERT are used to predict intensifiers in Malayalam sentences. Both models were trained to detect intensifiers using part-of-speech (POS) tags, and BERT regularly outperformed ...
R. Anitha, K.S. Anil Kumar, R.R. Rajeev
doaj   +1 more source