Triple

T575817
Position Surface form Disambiguated ID Type / Status
Subject Blink E13758 entity
Predicate supports P516 FINISHED
Object SVG E3757 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: SVG | Statement: [Blink, supports, SVG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SVG
Context triple: [Blink, supports, SVG]
  • A. 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.
  • B. XML
    XML (Extensible Markup Language) is a flexible, text-based markup language designed for structuring, storing, and transporting data in a platform-independent way.
  • C. SGML
    SGML (Standard Generalized Markup Language) is a standardized metalanguage for defining markup languages used to structure and describe the content of electronic documents.
  • D. Graphics Group
    Graphics Group was the computer graphics division of Lucasfilm that evolved into the pioneering animation studio later known as Pixar.
  • E. HTML5
    HTML5 is the fifth major version of the HyperText Markup Language standard, introducing modern web features such as semantic elements, native audio and video, and enhanced APIs for building rich, interactive web applications.
  • 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_69a4933fa4d88190a7949cc83c08c5c1 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49b67395c8190a8046ff7debe9d1f completed March 1, 2026, 8:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4ff4db0248190b2b3ca0290467313 completed March 2, 2026, 3:09 a.m.
Created at: March 1, 2026, 7:33 p.m.