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Chase and Provenance

Prometheux natively supports full explanations of logical processes for output generation in reasoning tasks via the materialization of the chase graph during its parallel and distributed evaluation. The chase graph mode is activated using the @chase annotation and is materialized into data sources such as CSV files or Neo4j databases.

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Configuring the Chase Graph

@chase("datasource", "filepath", "filename").

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Materializing to CSV

The chase graph is stored as a CSV dataset with columns: Fact, ProvenanceLeft, ProvenanceRight, Rule. 
arc(1,2).
arc(1,3).

path(X,Y) <- arc(X,Y).
@chase("csv", "disk/data", "chase.csv").
@output("path").
Output at disk/data/chase.csv: 
Fact,ProvenanceLeft,ProvenanceRight,Rule
"path(1,2)","arc(1,2)","","path(X,Y) <- arc(X,Y)"
"path(1,3)","arc(1,3)", "","path(X,Y) <- arc(X,Y)"

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Handling Aggregations

For programs with aggregations, intermediate chase nodes are introduced (prefixed with aggregated_explainability_): 
own(1,2,0.3).
own(1,2,0.4).
path_own(X,Y,Z) <- own(X,Y,Z), Z > 0.
path_own_agg(X,Y,C) <- path_own(X,Y,Z), C = msum(Z).
@chase("csv coalesce=true", "disk/data", "chase.csv").
@output("path_own_agg").

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Materializing for Neo4j Bulk Import

Set forNeo4jBulkImport=true to structure data for Neo4jā€™s bulk import tool: 
path(X,Y) <- arc(X,Y).
@chase("csv forNeo4jBulkImport=true, compression=gzip", "neo4j-import", "chase").
@output("path").
This produces separate node and edge CSV files. Import using: 
docker run --rm \
--volume=${PWD}/neo4j-data:/var/lib/neo4j/data \
--volume=${PWD}/neo4j-import:/var/lib/neo4j/import \
neo4j:4.4.31 \
neo4j-admin import --database=neo4j \
  --nodes=/var/lib/neo4j/import/chase/nodes/part-[a-zA-Z0-9\-]+.csv.gz \
  --relationships=/var/lib/neo4j/import/chase/edges/part-[a-zA-Z0-9\-]+.csv.gz

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Materializing to Neo4j (via Connector)

The chase graph is stored as a graph where each derivation creates a DERIVED_BY edge between CHASE_NODE nodes: 
arc(1,2).
arc(1,3).

path(X,Y) <- arc(X,Y).
@chase("neo4j", "", "").
@output("path").
Configure Neo4j in vada.properties: 
neo4j.chase.url=bolt://localhost:7687
neo4j.chase.username=neo4j
neo4j.chase.password=neo4j
neo4j.chase.database=neo4j

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Retrieving the Chase from Neo4j

@qbind("chase_neo4j", "neo4j", "\", "MATCH(n:CHASE_NODE) -[r:DERIVED_BY]->(m:CHASE_NODE) RETURN n.fact, m.fact, r.rule").
chase_edge(X,Y,R) <- chase_neo4j(X,Y,R).
@output("chase_edge").
For specific fact explanations using APOC traversal: 
@qbind("chase_neo4j", "neo4j", "\", "MATCH (root:CHASE_NODE {fact: 'a(1,2)' }) CALL apoc.path.subgraphNodes(root, {relationshipFilter: 'DERIVED_BY>', limit: 1000}) YIELD node MATCH (node)-[r]->(m) RETURN node.fact, m.fact, r.rule").
chase_edge(X,Y,R) <- chase_neo4j(X,Y,R).
@output("chase_edge").
Index the CHASE_NODE for better Neo4j performance:
CREATE INDEX index_chase_node__fact IF NOT EXISTS FOR (chase_node:CHASE_NODE) ON (chase_node.fact)