Triple

T4279521
Position Surface form Disambiguated ID Type / Status
Subject PostGIS E97115 entity
Predicate supportsFormat P203 FINISHED
Object KML E242853 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: KML | Statement: [PostGIS, supportsFormat, KML]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: KML
Context triple: [PostGIS, supportsFormat, KML]
  • A. KML chosen
    KML (Keyhole Markup Language) is an XML-based file format used to display geographic data and annotations in mapping applications such as Google Earth and Google Maps.
  • B. Geography Markup Language
    Geography Markup Language is an XML-based standard developed by the Open Geospatial Consortium for modeling, storing, and exchanging geographic information and spatial features.
  • C. MapInfo Professional
    MapInfo Professional is a desktop geographic information system (GIS) software application used for mapping, spatial analysis, and visualization of geographic data.
  • D. KGL
    KGL is the IATA airport code for Kigali International Airport, the main air gateway to Rwanda’s capital city.
  • E. KMLU
    KMLU is the ICAO airport code for Monroe Regional Airport, a public airport serving Monroe, Louisiana, in the United States.
  • 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_69b34544be3c819084d1ab82d29f90c5 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350367da48190b735deef9b5d2d2e completed March 12, 2026, 11:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b7b708b481908c1683741f84ee55 completed March 14, 2026, 7:32 p.m.
Created at: March 12, 2026, 11:07 p.m.