Describing Images Fast and Slow: Quantifying and Predicting the Variation in Human Signals during Visuo-Linguistic ProcessesTakmaz, Pezzelle, Fernández (2024)We use the spaCy library for tokenization, part-of-speech tagging, and lemmatization of the words in the descriptions.
displaCy.js: An open-source NLP visualizer for the modern webWith new offerings from Google, Microsoft and others, there are now a range of excellent cloud APIs for syntactic dependencies. A key part of these services is the interactive demo, where you enter a sentence and see the resulting annotation. We're pleased to announce the release of displaCy.js, a modern and service-independent visualization library. We hope this makes it easy to compare different services, and explore your own in-house models.
calamanCy: A Tagalog Natural Language Processing ToolkitMiranda (2023), EMNLP 2023We introduce calamanCy, an open-source toolkit for constructing NLP pipelines for Tagalog. It is built on top of spaCy, enabling easy experimentation and integration with other frameworks.
SyntaxNet in context: Understanding Google's new TensorFlow NLP modelYesterday, Google open sourced their Tensorflow-based dependency parsing library, SyntaxNet. The library gives access to a line of neural network parsing models published by Google researchers over the last two years. I've been following this work closely since it was published, and have been looking forward to the software being published. This post tries to provide some context around the release — what's new here, and how important is it?
A Good Part-of-Speech Tagger in about 200 Lines of PythonUp-to-date knowledge about natural language processing is mostly locked away in academia. And academics are mostly pretty self-conscious when we write. We’re careful. We don’t want to stick our necks out too much. But under-confident recommendations suck, so here’s how to write a good part-of-speech tagger.
Universal Dependencies v2.5 Benchmarks for spaCyWe present Universal Dependencies v2.5 benchmarks for spaCy v3.2 that show the competitive performance of spaCy in a direct comparison with Stanza and Trankit using the end-to-end evaluation from the CoNLL 2018 Shared Task.
