Explosion builds **developer tools** for AI, Machine Learning and Natural Language Processing. ### Project - [spaCy](/content/_/project/spacy/index.html) - [Prodigy](/content/_/project/prodigy/index.html) - [Ellf](/content/_/project/ellf/index.html) - [Thinc](/content/_/project/thinc/index.html) - [Consulting](/content/_/project/consulting/index.html) - [Case Study](/content/_/project/case_study/index.html) ### Topics - [LLMs](/content/_/topic/llms/index.html) - [NLP Strategy](/content/_/topic/strategy/index.html) - [Annotation](/content/_/topic/annotation/index.html) - [Biomedical](/content/_/topic/biomedical/index.html) - [Finance](/content/_/topic/finance/index.html) - [Media](/content/_/topic/media/index.html) - [Legal](/content/site-root.html) - [Humanities](/content/_/topic/humanities/index.html) - [Computer Vision](/content/_/topic/computer-vision/index.html) ### Category - [Blog](/content/_/category/blog/index.html) - [Release](/content/_/category/release/index.html) - [Universe](/content/_/category/universe/index.html) - [Talk](/content/_/category/talk/index.html) - [Interview](/content/_/category/interview/index.html) - [Video](/content/_/category/video/index.html) - [Paper](/content/_/category/paper/index.html) - [Book](/content/_/category/book/index.html) ### Tasks Select...Code GenerationCoreference ResolutionDependency ParsingDistillationEmbeddings & VectorsEntity LinkingEvaluationImage ClassificationImage SegmentationLayout AnalysisLemmatizationNamed Entity RecognitionObject DetectionOptical Character Recognition (OCR)Part-of-Speech TaggingPII AnonymizationQuestion AnsweringRelation ExtractionRetrieval-Augmented Generation (RAG)Rule-Based MatchingSpan CategorizationText ClassificationText GenerationTokenizationWeak Supervision ### Authors Select...Adriane BoydÁkos KádárBasile DuraChung-Fan TsaiDamian RomeroDaniël de KokDuygu AltinokEdward SchmuhlHelena SteckmeisterIndia KerleInes MontaniKabir KhanLj MirandaMadeesh KannanMagdalena AniołMatthew HonnibalPaul O’Leary McCannPeter BaumgartnerPhilip VolletRaphael MitschRehan AhmedRichard HudsonRyan WesslenSofie Van LandeghemVictoria SlocumVincent D. WarmerdamVinit RavishankarWalter Henry ## [How Love Without Sound helps the music industry recover millions in revenue for artists with NLP, spaCy and Prodigy](/content/blog/love-without-sound-nlp-music-industry/index.html) [A case study on Love Without Sound’s innovative AI-powered tools for the music industry and law firms specializing in royalty negotiations.](/content/blog/love-without-sound-nlp-music-industry/index.html) ## [Extracting Structured Information from Greek Legislation Data](https://repository.ihu.edu.gr/xmlui/handle/11544/30135) [Alexios (2023)](https://repository.ihu.edu.gr/xmlui/handle/11544/30135) [Worth noting is the existence of an application, called Prodigy, which takes advantage of an active learning framework and provides users with an interactive interface for data annotation.](https://repository.ihu.edu.gr/xmlui/handle/11544/30135) ## [uOttawa at LegalLens-2024: Transformer-based Classification Experiments](https://arxiv.org/abs/2410.21139) [Meghdadi, Inkpen (2024)](https://arxiv.org/abs/2410.21139) [Our training utilizes the spaCy pipeline configured with a transformer model and a transition-based parser for NER tasks. The deberta-v3-base model has been selected for the main transformer architecture.](https://arxiv.org/abs/2410.21139) ## [How We Found Pricey Provisions in New Jersey Police Contracts](https://www.propublica.org/article/how-we-found-pricey-provisions-in-new-jersey-police-contracts) [ProPublica](https://www.propublica.org/article/how-we-found-pricey-provisions-in-new-jersey-police-contracts) [ProPublica and the Asbury Park Press scoured hundreds of police union agreements for details on publicly funded payouts to cops, using spaCy under the hood.](https://www.propublica.org/article/how-we-found-pricey-provisions-in-new-jersey-police-contracts) ## [Simply Simplify Language](https://github.com/machinelearningZH/simply-simplify-language) [Interactive app by the Canton of Zurich, Switzerland, using LLMs and spaCy to analyze and simplify institutional communication and make bureaucratic German more inclusive.](https://github.com/machinelearningZH/simply-simplify-language) ## [Blackstone v0.1.15](https://github.com/ICLRandD/Blackstone) [A spaCy pipeline and model for NLP on unstructured legal text](https://github.com/ICLRandD/Blackstone) ## [Microsoft Presidio v2.2.352](https://github.com/microsoft/presidio) [Context aware, pluggable and customizable PII de-identification and anonymization service for text and images, featuring a spaCy back-end.](https://github.com/microsoft/presidio) ## [What 1.2 million parliamentary speeches can teach us about gender representation](https://pudding.cool/2018/07/women-in-parliament/) [The Pudding](https://pudding.cool/2018/07/women-in-parliament/) [Analysis of parliamentary speeches using spaCy.](https://pudding.cool/2018/07/women-in-parliament/) ## [Concepts and measures of bureaucratic constraints in European Union laws from hand-coding to machine-learning](https://onlinelibrary.wiley.com/doi/full/10.1111/rego.12543) [Franchino, Migliorati, Pagano, Vignoli (2023)](https://onlinelibrary.wiley.com/doi/full/10.1111/rego.12543) [The models “learn” the relations between the text tokens and the entity categories from two randomly selected samples of sentences that are extracted from a pre-processed corpus and have been manually annotated using the Python-implemented platform “Prodigy”.](https://onlinelibrary.wiley.com/doi/full/10.1111/rego.12543) ## [More than a Million Pro-Repeal Net Neutrality Comments were Likely Faked](https://hackernoon.com/more-than-a-million-pro-repeal-net-neutrality-comments-were-likely-faked-e9f0e3ed36a6) [Hackernoon](https://hackernoon.com/more-than-a-million-pro-repeal-net-neutrality-comments-were-likely-faked-e9f0e3ed36a6) [Analysis of net neutrality comments by Jeff Kao using spaCy for word vectors.](https://hackernoon.com/more-than-a-million-pro-repeal-net-neutrality-comments-were-likely-faked-e9f0e3ed36a6)