Triple

T17561190
Position Surface form Disambiguated ID Type / Status
Subject GDAL E427697 entity
Predicate usedBy P260 FINISHED
Object QGIS NE NERFINISHED

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 | Statement: [GDAL, usedBy, QGIS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: QGIS
Context triple: [GDAL, usedBy, QGIS]
  • 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. GRASS GIS
    GRASS GIS is an open-source geographic information system software suite used for geospatial data management, analysis, and visualization.
  • C. QGIS Server
    QGIS Server is a server-side application that renders and serves maps and geospatial data over the web using QGIS project files and styling.
  • D. GDAL
    GDAL is an open-source geospatial data abstraction library widely used for reading, writing, and transforming a broad range of raster and vector geographic data formats.
  • E. GIS
    The Egyptian General Intelligence Service (GIS) is Egypt’s primary intelligence agency responsible for foreign intelligence gathering, national security, and covert operations.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e0385081908a04b66f4dd4bd0d completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e456267e208190a1238fbe1a535bb0 completed April 19, 2026, 4:12 a.m.
Created at: April 10, 2026, 5:50 a.m.