Triple

T1831329
Position Surface form Disambiguated ID Type / Status
Subject Sugar Toolkit E40766 entity
Predicate relatedTo P37 FINISHED
Object Sugar desktop E203864 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: Sugar desktop | Statement: [Sugar Toolkit, relatedTo, Sugar desktop]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sugar desktop
Context triple: [Sugar Toolkit, relatedTo, Sugar desktop]
  • A. Sugar desktop environment chosen
    Sugar desktop environment is a child-friendly, activity-based graphical user interface originally developed for the One Laptop per Child project, designed to support collaborative and exploratory learning.
  • B. Sugar Toolkit
    Sugar Toolkit is a collection of libraries and tools used to develop educational activities and applications for the Sugar learning platform.
  • C. Puter
    Puter is one of the main regional dialects of the Romansh language, traditionally spoken in parts of the Engadine valley in Switzerland.
  • D. Sugar Labs
    Sugar Labs is a nonprofit organization that develops and maintains the Sugar learning platform, an open-source educational software environment originally created for the One Laptop per Child project.
  • E. Opera Software
    Opera Software is a Norwegian software company best known for developing the Opera web browser and related internet technologies.
  • 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_69a8864644bc8190b2358ab897194ac1 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb022aef48190975b6d12fc6681ad completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1c23f9c81909b7d524448351060 completed March 8, 2026, 7:45 p.m.
Created at: March 4, 2026, 7:32 p.m.