Triple

T8608752
Position Surface form Disambiguated ID Type / Status
Subject Mutter E203867 entity
Predicate supports P516 FINISHED
Object XWayland
XWayland is a compatibility layer that allows traditional X11 applications to run seamlessly within Wayland-based display servers.
 E745760 NE FINISHED

How this triple was built (4 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: XWayland | Statement: [Mutter, supports, XWayland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XWayland
Context triple: [Mutter, supports, XWayland]
  • A. Wayland
    Wayland is a modern display server protocol for Linux and other Unix-like systems designed to replace the X Window System with a simpler, more efficient architecture.
  • B. Wayland
    Wayland is a small city in Allegan County, Michigan, known for its rural character and proximity to Grand Rapids.
  • C. wlroots
    wlroots is a modular, compositor-focused library that provides building blocks for creating Wayland compositors, widely used in lightweight and tiling window managers.
  • D. Chromium (Wayland backend)
    Chromium (Wayland backend) is a build and configuration of the Chromium web browser that uses the Wayland display protocol for native windowing and graphics on Linux systems.
  • E. Xinerama
    Xinerama is an X Window System extension that enables multi-monitor support by combining multiple physical displays into a single large virtual screen.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: XWayland
Triple: [Mutter, supports, XWayland]
Generated description
XWayland is a compatibility layer that allows traditional X11 applications to run seamlessly within Wayland-based display servers.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XWayland
Target entity description: XWayland is a compatibility layer that allows traditional X11 applications to run seamlessly within Wayland-based display servers.
  • A. Wayland
    Wayland is a modern display server protocol for Linux and other Unix-like systems designed to replace the X Window System with a simpler, more efficient architecture.
  • B. Wayland
    Wayland is a small city in Allegan County, Michigan, known for its rural character and proximity to Grand Rapids.
  • C. wlroots
    wlroots is a modular, compositor-focused library that provides building blocks for creating Wayland compositors, widely used in lightweight and tiling window managers.
  • D. Chromium (Wayland backend)
    Chromium (Wayland backend) is a build and configuration of the Chromium web browser that uses the Wayland display protocol for native windowing and graphics on Linux systems.
  • E. Xinerama
    Xinerama is an X Window System extension that enables multi-monitor support by combining multiple physical displays into a single large virtual screen.
  • F. None of above. chosen

Provenance (5 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_69ca832c23e4819095a9f3eea4a21828 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc46ed77588190a872d22d9d1f7429 completed March 31, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea90dd93081908140ac0ce23be820 completed April 2, 2026, 5:36 p.m.
NEDg Description generation batch_69ceaa2c34308190a3bc7717012fea9d completed April 2, 2026, 5:41 p.m.
NED2 Entity disambiguation (via description) batch_69ceaae76d188190932826c9fd9f7f5f completed April 2, 2026, 5:44 p.m.
Created at: March 30, 2026, 6:25 p.m.