textacy

Thanks! Comparison between news outlets is on the radar, once I improve the tool based on feedback from this Show HN. My backend uses spaCy (NER/NLP), textacy [1] for extracting subject-verb-object triples, and coreferee [2] for coreference resolution. I did build a custom spaCy model for which I manually annotated over 700 crash-related news articles in Label Studio [3]. This custom model identifies counterfactuals, framing (e.g. thematic elements), and what's called CARLIKE, because vehicles can be referred to in so many ways (year-make-model, year-model, color model, generic terms like pickup/sedan/truck, nicknames like Chevy instead of Chevrolet, etc. Coreference resolution was probably my favorite part of the NLP analyzer. For example: "A woman was injured after being struck by a vehicle. She was walking on Washington Street when the

I love textacy, it has soo much out of the box. Topic modeling, topic extraction, summarization, and its built on top of Spacy. https://github.com/chartbeat-labs/textacy

I love Spacy, and recently discovered Textacy: "higher-level NLP built on Spacy"[1]. It's pretty good. [1] https://github.com/chartbeat-labs/textacy

Check out textacy, a higher-level text library built on top of spaCy, for better keywords extraction: https://github.com/chartbeat-labs/textacy https://textacy.readthedocs.io/en/latest/api_reference.html#...