Recognising non-named spatial entities in literary texts: a novel spatial entities classifierKababgi, Grisot, Pennino, Herrmann (2024)In this paper, we present a case study on the prediction of what we call ‘non-named spatial entities’ (NNSE) in a historical corpus of Swiss-German novels using a deep learning model in conjunction with BERT and Prodigy.
Impoliteness and morality as instruments of destructive informal social control in online harassment targeting Swedish journalistsBjörkenfeldt, Gustafsson (2023)In the annotation tool Prodigy used for this process, the tweets directed towards journalists were displayed alongside the initial tweet that initiated the conversation thread and the subsequent reply from the journalist.
Speech acts in the Dutch COVID-19 Press ConferencesSchueler, Marx (2022), Language Resources and EvaluationWe used the annotation tool Prodigy. Prodigy provides a simple interface in which the annotator sees a sentence and selects the applicable speech acts. The use of Prodigy considerably sped up the annotation process, allowing the annotators to annotate around 200 sentences per hour.
Assessing Fine-Tuned NER Models with Limited Data in French: Automating Detection of New Technologies, Technological Domains, and Startup Names in Renewable EnergyMacLean, Cavallucci (2024)In order to assure the uniformity of the process of fine-tuning each model, we decided to use the spaCy library. This library, one of the most widely used for NLP tasks, allows us to directly modify a simple configuration file in order to define the model.
Toward a Critical Toponymy Framework for Named Entity Recognition: A Case Study of Airbnb in New York CityBrunila, LaViolette, CH-Wang, Verma, Féré, McKenzie (2023), EMNLP 2023All annotation was performed using Prodigy following an initial training session where annotators collaboratively annotated a randomly chosen set of samples.
Creating Custom Event Data Without Dictionaries: A Bag-of-TricksHalterman, Schrodt, Beger, Bagozzi, Scarborough (2023)While in the past the process of generating training case has been quite time consuming and tedious, newer approaches such as those incorporated into the web-based Prodigy annotation system allow this to be done much more quickly.
Solutions for Advanced NLP for Diverse LanguagesNew Languages for NLP KeynoteThis talk discusses spaCy’s philosophy for modern NLP, its extensible design and new recent features to enable the development of advanced natural language processing pipelines for typologically diverse languages.
Explosion awarded META Seal of RecognitionWe’re proud to accept the META Seal of Recognition at META-FORUM in Brussels, along with Mozilla. The META-FORUM is an international conference series backed by the European Union on powerful and innovative Language Technologies for a multilingual information society.
Towards Structured Data: LLMs from Prototype to ProductionU.S. Census Bureau: Center for Optimization and Data Science SeminarThis talk presents pragmatic and practical approaches for how to use LLMs beyond just chat bots, how to ship more successful NLP projects from prototype to production and how to use the latest state-of-the-art models in real-world applications.
How Good is the Model in Model-in-the-loop Event Coreference Resolution Annotation?Ahmed, Nath, Regan, Pollins, Krishnaswamy, Martin (2023)Figure 6 illustrates the interface design of the annotation methodology on the popular model-in-the-loop annotation tool - Prodigy. We use this tool for the simplicity it offers in plugging in the various ranking methods we explained.
Applied Language TechnologyExtensive online course on applied language technology with spaCy by Tuomo Hiippala, designed for students new to NLP and programming.
Zero-Shot NER with GliNER and spaCy Python Tutorials for Digital HumanitiesTutorial by WJB Mattingly on how to integrate the generalist GLiNER model for Named Entity Recognition with spaCy's versatile NLP environment.
SpanCat with spaCy and Prodigy on real dataYouTube series by WJB Mattingly showing an end-to-end project, from cultivating and annotating data to training, testing and visualizing a model.
The triangulation of ethical leader signals using qualitative, experimental, and data science methodsBanks, Ross, Toth, Tonidandel, Goloujeh, Dou, Wesslen (2022)This additional text was labeled by the same coding team using Prodigy, [...] a flexible user interface tool built on top of spaCy, a leading open source library in python for natural language processing. We created a spaCy end‐to‐end project workflow including package versioning, data pre‐processing, data ingestion into a database, annotation sessions using Prodigy’s user interface, model training, model evaluation, python packaging, and visual app for testing the model.
Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat ViolenceHalterman, Keith, Sarwar, O’Connor (2021), ACL 2021Figure A2 shows a stylized version of the custom interface we built using the Prodigy annotation tool. Annotators are presented with an entire document, with sentences sequentially highlighted.
