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What it does

Runs the temporal variant of the cognify pipeline: instead of (or in addition to) standard entity/relationship extraction, it extracts events and timestamps so the knowledge graph supports temporal reasoning. Mirrors Python’s temporal_cognify=True.

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When to use it

  • Your corpus is event-driven (logs, meeting notes, news, changelogs) and you want to ask “what happened when?” / “what came before X?”.
  • You plan to query with temporal recall (see below).

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CLI

cognee-cli cognify -d my_dataset --temporal-cognify
The flag is --temporal-cognify (crates/cli/src/cli.rs, CognifyArgs). It maps to CognifyConfig.temporal_cognify.

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Programmatic

use cognee_cognify::CognifyConfig;

let config = CognifyConfig::default()
    .with_temporal_cognify(true);
// also: .with_data_per_batch(n) tunes the temporal batch size (default 20)
See CognifyConfig (temporal_cognify, with_temporal_cognify, data_per_batch).

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Querying temporal memory

Retrieve with the TEMPORAL search type: 
cognee-cli search "what happened before the launch?" -t TEMPORAL -d my_dataset
# or let recall auto-route to a temporal strategy:
cognee-cli recall "timeline of the project"
This uses SearchType::Temporal and the temporal retriever (crates/search/src/). The recall router can auto-select the temporal strategy from the query (crates/search/src/query_router.rs).

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Pointers