#textAnnotation

HabileDatahabiledata
2025-06-13

Future Trends In Text Annotation Automation and AI Enhancement

As AI evolves, so does the way we train it. Explore how automation is transforming the future of text annotation and what it means for accuracy and scalability.

Read the full article here:

hitechbpo.medium.com/future-tr

HabileDatahabiledata
2025-05-31

How To Remove Bias And Ambiguity In Text Annotation For Machine Learning

Want to improve your machine learning outcomes? Start by fixing what goes in.

Learn best practices, common pitfalls, and how expert annotators make the difference.
Read more:

shorturl.at/Xrbae

HabileDatahabiledata
2025-04-18

Boost Your Text Annotation with Next-Gen NLU Technology

From sentiment analysis to chatbot training, advanced NLU ensures more precise and efficient text processing.

🔹 Improved contextual understanding for AI models
🔹 Faster and more accurate text annotation

Check how next-gen NLU technology is revolutionizing text annotation:
shorturl.at/0Ylfs

HabileDatahabiledata
2025-04-10

Enhance AI with Accurate Text Annotation for News Articles

Our expertise in text annotation helped structure vast amounts of news for AI models, improving sentiment analysis, content categorization, and automated summaries. With precise labeling, we empower AI-driven insights for media intelligence and research.

Discover how our text services refine AI models: shorturl.at/cu71a

Staatsbibliothek zu Berlinstabi_berlin@openbiblio.social
2025-01-29

Meistert mit uns die Herausforderungen der automatischen #Textannotation historischer Sprachen: In unserem Online- #Workshop "Automatische Annotation von Kirchenslavica mit Stanza" (Mo., 10. Februar) lernt ihr, wie ihr mit der #Python-Bibliothek #Stanza eure Kenntnisse im Bereich Natural Language Processing (#NLP) mit einem Fokus auf die Annotation von #Kirchenslavica erweitern könnt 👉 blog.sbb.berlin/online-worksho

Infosearch BPOinfosearch_bpo
2024-06-25

What is data annotation, and why is it important for AI / ML success?
infosearchbpo.com/bpo-news/wha

Infosearch offers various annotation types (image, text, video, audio etc) and techniques (bounding boxes, polygon, cuboid etc).
infosearchbpo.com/annotation-s

Email us at enquiries(@)infosearchbpo(.)com to outsource your data annotation services.

Richard ECKART DE CASTILHOreckart@fosstodon.org
2024-06-25

⚡️INCEpTION 33.1 - the text annotation platform - is out now and improves the stability of the annotation editor as well as introducing a few minor features. In particular if you are using 33.0 now, you should consider upgrading.

github.com/inception-project/i

#inceptiontap #opensource #textannotation

2024-05-07

Looks like we've reached the "let's polish the UI animations" phase of development 🚀 #Recogito #ImageAnnotation #TextAnnotation

Richard ECKART DE CASTILHOreckart@fosstodon.org
2023-12-05

⚡️ INCEpTION 30.0 is out now! Improved project creation workflow, consistent annotation detail popup across all editors, and more... github.com/inception-project/i #inceptiontap #opensource #textannotation

Lukas Isermannliserman@mstdn.social
2023-08-10

Thread:
🚨Software Publication Alert🚨
This one is for you, text-analysis folks:

I am very happy to share the publication of my text annotation R-package "handcodeR" 🥳, which is now available on CRAN. 🧵1/7

CRAN.R-project.org/package=handcoge=handcodeR

#CRAN #rstats #TextAsData #TextAnnotation

Picture of Text Annotation App
2023-04-07

#RecogitoJS is about to get a major update, soon-ish. #Annotation #TextAnnotation

Erik JonkerErikJonker
2023-03-31

Interesting but not surprising at all, this is a typical task you would want to use these models for: "ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks" , it could give an enormous boost to annotation of data, which can be used for AI training. Further reinforcing the speed of AI development. Footnote, this was done with GPT3.5 not with GPT4 that is available now and better.

arxiv.org/abs/2303.15056

2022-12-15

New Results for the Text Recognition of Arabic Maghribī Manuscripts - Managing an Under-resourced Script

by Noëmie Lucas, Clément Salah and Chahan Vidal-Gorène (2021)

Paper: arxiv.org/ftp/arxiv/papers/221
RASAM dataset on Github: github.com/calfa-co/rasam-data

#htr #arabic #maghribi #calfa #calfavision #rasam #textannotation @islamicstudies

HTR models development has become a conventional step for digital humanities projects. The performance of these models, often quite high, relies on manual transcription and numerous handwritten documents. Although the method has proven successful for Latin scripts, a similar amount of data is not yet achievable for scripts considered poorly-endowed, like Arabic scripts. In that respect, we are introducing and assessing a new modus operandi for HTR models development and fine-tuning dedicated to the Arabic Maghribī scripts. The comparison between several state-of-the-art HTR demonstrates the relevance of a word-based neural approach specialized for Arabic, capable to achieve an error rate below 5% with only 10 pages manually transcribed. These results open new perspectives for Arabic scripts processing and more generally for poorly-endowed languages processing. This research is part of the development of RASAM dataset in partnership with the GIS MOMM and the BULAC.

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