Triple

T11957264
Position Surface form Disambiguated ID Type / Status
Subject GLX E284583 entity
Predicate hasExtensionMechanism P11253 FINISHED
Object GLX extensions E284583 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: GLX extensions | Statement: [GLX, hasExtensionMechanism, GLX extensions]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GLX extensions
Context triple: [GLX, hasExtensionMechanism, GLX extensions]
  • A. GLX chosen
    GLX is the OpenGL Extension to the X Window System that enables rendering OpenGL graphics within X11-based applications.
  • B. Xinerama
    Xinerama is an X Window System extension that enables multi-monitor support by combining multiple physical displays into a single large virtual screen.
  • C. X11
    X11 is a widely used windowing system and network-transparent graphical protocol that provides the foundational GUI framework for Unix-like operating systems.
  • D. EGL
    EGL is the station code used to identify Eglinton station in transit systems and related services.
  • E. EGL
    EGL is an interface between Khronos rendering APIs like OpenGL ES and the native windowing system, enabling efficient rendering and context management on a variety of platforms.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903681a00819098c2b5260e2ef834 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f459210d1c8190953cd01da3d2ad04 completed May 1, 2026, 7:41 a.m.
Created at: April 8, 2026, 9:45 p.m.