I'm impressed with Cortex - All industry leaders (Google, Siri, Alexa) answer "Who killed John Wilkes Booth" with "Abraham Lincoln," but this gives the correct answer. It shows that it has a deeper understanding of it's data sources.
I asked "What is taller, a dog or a giraffe?" and it didn't know. Common sense is not yet in the knowledge graph. Maybe it can't perform comparisons Also: "What is the largest city in Europe?" -> "New York City". "What is the largest city in the world?" -> "Gotham City" So it seems to make KB lookup errors and probably can't do logic/set operations.
Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
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Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#12Ignore the grammar error, you're helping government extract information from text? Where exactly? Do you mean the NSA? Do you mean helping the government look at public internet written commentary to track citizens?
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#13I'm impressed with Cortex - All industry leaders (Google, Siri, Alexa) answer "Who killed John Wilkes Booth" with "Abraham Lincoln," but this gives the correct answer. It shows that it has a deeper understanding of it's data sources.
Winnie - The - Pooh
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#14"We're make sense of dark data to help companies in technology, law, medicine, and government extract information from text." Ignore the grammar error, you're helping government extract information from text? Where exactly? Do you mean the NSA? Do you mean helping the government look at public internet written commentary to track citizens?
We don't do anything like that, in fact, we don't work with the government at all right now. We know that there is a huge application of this technology in the government beyond the Department of Defense. For example, large corpuses of text data other government agencies might need to process like the Census Bureau, the IRS, etc.
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#15I'm impressed with Cortex - All industry leaders (Google, Siri, Alexa) answer "Who killed John Wilkes Booth" with "Abraham Lincoln," but this gives the correct answer. It shows that it has a deeper understanding of it's data sources.
> What is the most dangerous bear? Winnie - The - Pooh
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#16Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#17It feels like you've reinvented much by writing stuff from scratch. spaCy is fast, has tons of features, commonly updated, free, trained on the Common Crawl corpus. Why not just use that? I'm only curious, not critical.
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#18Can the lingua component of this (when it is available) be used to answer questions from my own text corpus?
Re: Launch HN: Plasticity (YC S17) – APIs for human-like natural language interfaces
#19Something I'll keep my eye on, for sure. In the meantime: It feels like you've reinvented much by writing stuff from scratch. spaCy is fast, has tons of features, commonly updated, free, trained on the Common Crawl corpus. Why not just use that? I'm only curious, not critical.
Fair question, we think spaCy is great, but it just made a lot of sense for us to start on the basics so that we could modify things as needed. For example, our tokenization algorithm and syntax dependency tree algorithm treats "let it be" in "The band played let it be by the beatles." as a single chunk to return a more accurate syntax dependency tree, which Google Cloud NL and spaCy don't do out of the box today.