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Semantic extraction pipeline

Project · Key work

Semantic extraction pipeline is a Python pipeline he built during his joint research at JAIST in 2025. It extracts structured semantic facts for safety testing of automated driving systems, alongside the ADS safety-testing ontology.

How it ran

  • Validation: the extracted facts were checked with SPARQL queries.
  • Scale: the work ran on JAIST's KAGAYAKI HPC and PBS job orchestration cluster as batch jobs submitted through PBS, the cluster's job scheduler.

The PBS commands he used there (qsub, qstat, qdel) later turned up as shortcuts in his command-line tool mops.

See also

In the knowledge graph

Semantic extraction and the 12 things it is linked to. Open any dot for its page, or explore it in the full graph.

As data

Everything on this page is read from triples in the knowledge graph. These are the 21 it states about Semantic extraction, and 3 more its ontology implies; the console runs SPARQL over the whole graph, here in your browser.

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@prefix id: <https://ask.chaipat.cc/id/> .
@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> .
@prefix cj: <https://ask.chaipat.cc/ns#> .
@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> .
@prefix xsd: <http://www.w3.org/2001/XMLSchema#> .

id:SemanticExtraction
    a cj:Project ;
    cj:theme id:ThemeOntology ;
    rdfs:label "Semantic extraction pipeline" ;
    cj:shortLabel "Semantic extraction" ;
    cj:context id:JAIST ;
    cj:during id:RoleJAIST ;
    cj:uses id:SPARQL , id:Python , id:HPC ;
    cj:cluster "KAGAYAKI HPC cluster" ;
    cj:description "Pipeline that extracts semantic facts for ADS safety testing, validated with SPARQL and run as PBS jobs." ;
    cj:featured true ;
    cj:tier 1 ;
    cj:keyRank 2 ;
    cj:integrates id:PBSScheduler ;
    cj:runsOn id:KAGAYAKI ;
    cj:relatedTo id:ADSOntology ;
    cj:mentions id:KGFromText , id:MopsCli ;
    cj:article "https://ask.chaipat.cc/wiki/SemanticExtraction"^^xsd:anyURI ;
    cj:activeIn id:Y2025 .
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