Triple

T5167217
Position Surface form Disambiguated ID Type / Status
Subject OpenGL E116587 entity
Predicate relatedStandard P37 FINISHED
Object WebGL E72103 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: WebGL | Statement: [OpenGL, relatedStandard, WebGL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WebGL
Context triple: [OpenGL, relatedStandard, WebGL]
  • A. WebGL chosen
    WebGL is a JavaScript API that enables hardware-accelerated 2D and 3D graphics rendering within web browsers without the need for plugins.
  • B. WebGPU
    WebGPU is a modern web graphics and compute API designed to provide high-performance, low-level access to GPU capabilities in browsers, succeeding and improving upon WebGL.
  • C. WGL
    WGL is the common abbreviation for the Leibniz Association, a major German network of non-university research institutes spanning a wide range of scientific disciplines.
  • D. OpenGL ES
    OpenGL ES is a cross-platform, royalty-free 2D and 3D graphics API designed for embedded systems such as mobile devices, game consoles, and automotive displays.
  • E. OpenGL
    OpenGL is a cross-language, cross-platform application programming interface (API) for rendering 2D and 3D vector graphics, widely used in games, simulations, and professional visualization.
  • 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_69bd445ff97c81909a2615cc56235470 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd792c5ea88190b6aa0e519c744155 completed March 20, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed93b85188190927d448e09a46425 completed March 21, 2026, 5:45 p.m.
Created at: March 20, 2026, 1:45 p.m.