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Knowledge graphs for text (the focus of the article) seem narrowly-scoped since they require "objective" facts and relations to be practical. Capturing the subj
by physicsgraph 5y ago
Knowledge graphs for text (the focus of the article) seem narrowly-scoped since they require "objective" facts and relations to be practical. Capturing the subjective and transient perspective of observations made by multiple observers (which is what we actually have access to) is more complicated.
For example, asking the same person the same question may yield different answers based on their mood or other environmental or situational factors. Who's asking the question can also matter, as does the specific phrasing of the question.
- 0xbadcafebee 5y agoYou could use knowledge graphs to help solve those problems too. Objective fact is just a seemingly simpler domain to work in. Subjectivity is still based on objective facts, it's just a whole lot more of them that are subtler and harder to detect.
- KhoomeiK 5y agoRecent work suggests it's possible to generate knowledge graphs from large corpi of text encoded with a language model: https://arxiv.org/abs/2010.11967 https://arxiv.org/abs/2010.11967
- axiom92 5y agoSimilar work (I'm the first author): generating temporal graphs from text using language models https://arxiv.org/pdf/2010.10077.pdf https://arxiv.org/pdf/2010.10077.pdf.
- blackcat201 5y agoI wouldn't recommend using this work to generate knowledge graphs, as it requires a lot of rule based filtering. I suspect it wouldn't be any better than generating from a constituency parse tree. Disclaimer, I implemented this work a while ago and reach my current conclusion, still waiting for the official code to release.