Description
I am analyzing your ingestion pipeline (specifically tracing the flow from raw source data/episodes through extraction and final bulk persistence). While your prompt engineering and extraction layers are incredibly sophisticated at managing graph topology and edge-fragmentation rules, there is an open architectural opportunity regarding semantic memory hygiene.
The Structural Gap
During multi-party dialogues or entries involving third parties (e.g., "My brother is a lawyer"), upstream LLMs can occasionally misattribute entity relationships during the initial extraction pass.
Currently, there is no deterministic middleware hook or validation callback phase between the resolution of these graph elements and their final bulk persistence to verify if the extracted triples remain semantically faithful to the raw input string.
An Open Question on Topology Pressures
Because graph optimization rules naturally pressure the model to prefer direct entity paths and drop scenery nouns, I am curious if the maintainers have noticed this compaction pressure occasionally collapsing human intermediaries (e.g., accidentally collapsing a relationship through a "colleague" directly into the primary User entity).
Proposed Solution
I want to propose an opt-in validator hook interface right before records are committed to the graph database:
async def verify_graph_hygiene(extracted_edges: list, source_text: str) -> list:
# Local NLI/Attribution filtering runs here out-of-band
return verified_edges
graph = Client(config={
"ingest_validator": verify_graph_hygiene
})Does an ingestion-time interceptor contract align with your architectural roadmap, and would you be open to a minimal PR exploring this hook structure?
Description
I am analyzing your ingestion pipeline (specifically tracing the flow from raw source data/episodes through extraction and final bulk persistence). While your prompt engineering and extraction layers are incredibly sophisticated at managing graph topology and edge-fragmentation rules, there is an open architectural opportunity regarding semantic memory hygiene.
The Structural Gap
During multi-party dialogues or entries involving third parties (e.g., "My brother is a lawyer"), upstream LLMs can occasionally misattribute entity relationships during the initial extraction pass.
Currently, there is no deterministic middleware hook or validation callback phase between the resolution of these graph elements and their final bulk persistence to verify if the extracted triples remain semantically faithful to the raw input string.
An Open Question on Topology Pressures
Because graph optimization rules naturally pressure the model to prefer direct entity paths and drop scenery nouns, I am curious if the maintainers have noticed this compaction pressure occasionally collapsing human intermediaries (e.g., accidentally collapsing a relationship through a "colleague" directly into the primary User entity).
Proposed Solution
I want to propose an opt-in validator hook interface right before records are committed to the graph database:
Does an ingestion-time interceptor contract align with your architectural roadmap, and would you be open to a minimal PR exploring this hook structure?