nostr:npub1z0pekk9ueskyxmhnlq2jmquhc87ycnam0j87mnyt30h0h4n6udfs4dd6zw
2/3
* this work is thus more proof of concept effort
* biomed literature / domain complex: unknown level of this expertise among authors
* that said v. interesting PoC
* would be interesting to see LLM triple-based KG, auto fact-checked (parts-of-speech? coreference resolution the hard issue)
* will be nice to see how this plays out; imo, structured KG (ontological; topics) tremendously important/usefu !
* noise always an issue, as well (in health) transparency, explainability
nostr:npub1z0pekk9ueskyxmhnlq2jmquhc87ycnam0j87mnyt30h0h4n6udfs4dd6zw
3/3
Can large language models build causal graphs?
https://arxiv.org/abs/2303.05279
Establishing Trust in ChatGPT BioMedical Generated Text: An Ontology-Based Knowledge Graph to Validate Disease-Symptom Links
https://arxiv.org/abs/2307.01128
AI and the transformation of social science research
Careful bias management and data fidelity are key
nostr:npub1z0pekk9ueskyxmhnlq2jmquhc87ycnam0j87mnyt30h0h4n6udfs4dd6zw
4/4
Construction of Knowledge Graphs: State and Challenges
https://arxiv.org/abs/2302.11509
Machine Knowledge: Creation and Curation of Comprehensive Knowledge Bases
https://arxiv.org/abs/2009.11564
A Framework for Large Scale Synthetic Graph Dataset Generation
