Triple

T11060054
Position Surface form Disambiguated ID Type / Status
Subject QGIS E261485 entity
Predicate developer P73 FINISHED
Object QGIS community E261485 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: QGIS community | Statement: [QGIS, developer, QGIS community]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: QGIS community
Context triple: [QGIS, developer, QGIS community]
  • A. QGIS chosen
    QGIS is a free, open-source geographic information system application used for viewing, editing, and analyzing geospatial data across multiple platforms.
  • B. Python community
    The Python community is the global network of developers, users, and contributors who collaboratively build, maintain, and advance the Python programming language and its ecosystem.
  • C. Open Source Geospatial Foundation
    The Open Source Geospatial Foundation (OSGeo) is a nonprofit organization that supports and promotes open-source geospatial software, data, and education worldwide.
  • D. KDE community
    The KDE community is an international, volunteer-driven group that collaborates to create free and open-source desktop environments, applications, and frameworks for Linux and other platforms.
  • E. Jupyter community
    The Jupyter community is an open, collaborative group of developers, researchers, and educators who build and maintain the Jupyter ecosystem for interactive computing and data science.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d6aa98650481908609c7c56bfa7902 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d798e991848190b07c2f48dae38681 completed April 9, 2026, 12:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3c87ab0308190a6a6ada1708f0ec2 completed April 18, 2026, 6:07 p.m.
Created at: April 8, 2026, 9:26 p.m.