Explosion builds developer tools for AI, Machine Learning and Natural Language Processing.
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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
A modern approach and mindset for building future-proof NLP pipelines in-house, focusing on use cases from banking, finance and economics.
A Prodigy case study of Posh AI's production-ready annotation platform and custom chatbot annotation tasks for banking customers.
A case study on Love Without Sound’s innovative AI-powered tools for the music industry and law firms specializing in royalty negotiations.
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.
A case study on S&P Global’s efficient information extraction pipelines for real-time commodities trading insights in a high-security environment.
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.
Project from teams at The Times and BBC using spacy-llm to make complex financial interests data more accessible.
I relied on the text annotation software Prodigy in Python that offers a friendly user interface where the reviewer can read the text and assign a label to each paragraph.