implementation detail · filed under data curation
Agentic knowledge graph construction
A directed acyclic knowledge graph is expanded recursively from coarse seed nodes, with agents searching the web for each node’s concept.
- source
- 1
- model
- 1
- lab adopt it
- 1
- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
We construct the knowledge graph as a directed acyclic graph through recursive, agent-driven expansion. The expansion process begins with a predefined set of coarse-grained seed nodes. An agent instance is then assigned to each node and performs multiple web searches to investigate the corresponding concept.
usedunclearin Kimi K3Moonshot AI
Filed alongside
Other methods under data curation :: data sourcing.
Expert co-created training dataGitHub CrawlCommon CrawlEssentialWebFinePDFsHigh-recall web-data curationImage-code pairs and computer-use trajectoriesLong-document curationNemotron-3-Ultra corpusNemotron-CCNemotron-Post-Training-v3Star-threshold-filtered GitHub repositoriesStreaming training-data ingestionVideo frame extraction at 1 FPSVideo sampling parametersWeb knowledge graph construction and question generation