Triple

T17560917
Position Surface form Disambiguated ID Type / Status
Subject WKB E427693 entity
Predicate usedBy P260 FINISHED
Object PostGIS 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: PostGIS | Statement: [WKB, usedBy, PostGIS]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: PostGIS
Context triple: [WKB, usedBy, PostGIS]
  • A. PostGIS chosen
    PostGIS is an open-source spatial database extender that adds robust geographic object support and spatial querying capabilities to PostgreSQL.
  • B. SpatiaLite
    SpatiaLite is an open-source spatial extension to the SQLite database engine that adds support for storing and querying geospatial data.
  • C. MySQL spatial extensions
    MySQL spatial extensions are a set of features in the MySQL database that enable storage, indexing, and querying of geometric and geographic data using standard spatial formats and functions.
  • D. Oracle Spatial
    Oracle Spatial is an extension to the Oracle Database that provides advanced spatial data storage, indexing, and analysis capabilities for geographic information systems and location-based applications.
  • E. cuSpatial
    cuSpatial is a GPU-accelerated spatial and GIS analytics library within NVIDIA RAPIDS designed to perform high-performance geospatial data processing.
  • 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.