Triple

T17561025
Position Surface form Disambiguated ID Type / Status
Subject GeoServer E427695 entity
Predicate supportsFormat P203 FINISHED
Object SVG 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: SVG | Statement: [GeoServer, supportsFormat, SVG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SVG
Context triple: [GeoServer, supportsFormat, SVG]
  • A. SVG
    SVG is the three-letter IATA airport code assigned to Stavanger Airport, Sola in Norway.
  • B. SVG chosen
    SVG (Scalable Vector Graphics) is an XML-based vector image format for two-dimensional graphics that supports interactivity and animation, widely used for web graphics due to its scalability and resolution independence.
  • C. SVG Air
    SVG Air is a regional airline based in Saint Vincent and the Grenadines that operates scheduled and charter flights throughout the Eastern Caribbean.
  • D. Vector Graphic
    Vector Graphic was an early microcomputer company known for producing S-100 bus–based personal computers during the late 1970s and early 1980s.
  • E. Inkscape
    Inkscape is a free, open-source vector graphics editor known for creating and editing scalable illustrations, logos, and diagrams.
  • 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.