Earlier quoted context omitted.
FYI I updated the visualization. Credit goes to @jacomyal from @ouestware on GitHub who helped me out.
The "Chloé Woestelandt" test is still just as bad
I see this: https://imgur.com/a/SGnbXjG
Show HN: Knowledge graph of restaurants and chefs, built using LLMs
41–45 of 45 posts
Re: Show HN: Knowledge graph of restaurants and chefs, built using LLMs
#42Earlier quoted context omitted.
The "Chloé Woestelandt" test is still just as bad
I see this: https://imgur.com/a/SGnbXjG
Yes! This looks amazing. Thanks!
I made a mistake; I had checked the other link in your post ("You can explore the visualization here: [Interactive Culinary Network]") instead of the main link.
Re: Show HN: Knowledge graph of restaurants and chefs, built using LLMs
#43Given the structured nature of the data, how does this compare to running a specialized classification model that looks for specific words in a review and uses those to assign Chefs to Restaurants? With some fine tuning, you might get more consistent results than feeding the reviews into a generative model.
The data is initially not at all structured, and the critics talk about a chef's CV in passing. For instance, take this example: > At Grenat, Antoine Joannier and Neil Mahatsry are bathed in an ardent red glow, much like the pomegranate-toned walls of their space. After working together at La Brasserie Communale, where they first met, the duo is now firing on all cylinders in the heart of Marseille, where Antoine ten…
LLMs have without a doubt replaced NER models and libraries like SpaCy. At least for my use-cases, creating ontologies and populating knowledge graphs.
Re: Show HN: Knowledge graph of restaurants and chefs, built using LLMs
#44This looks great! I was just looking for a good web knowledge graph visualizer.
All credit goes to gephi-lite [1] and the sister project Retina [2].
[1] https://gephi.org/gephi-lite/ [2] https://ouestware.gitlab.io/retina/1.0.0-beta.4/
Re: Show HN: Knowledge graph of restaurants and chefs, built using LLMs
#45Do you think this will work as effectively with Google or Social Media review and rating datasets? As every country may not have a LeFooding.com
Would like to here everyone's thoughts