Triple

T12325625
Position Surface form Disambiguated ID Type / Status
Subject SCORM E293821 entity
Predicate version P3286 FINISHED
Object SCORM 2004 E293821 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: SCORM 2004 | Statement: [SCORM, version, SCORM 2004]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SCORM 2004
Context triple: [SCORM, version, SCORM 2004]
  • A. SCORM chosen
    SCORM is a widely used e-learning standard that defines how online learning content and learning management systems communicate and track learner progress.
  • B. Adobe Captivate
    Adobe Captivate is an eLearning authoring tool used to create interactive software simulations, quizzes, and responsive training content for web and mobile delivery.
  • C. LTI
    LTI (Learning Tools Interoperability) is an education technology standard that enables seamless integration of external learning applications and tools into learning management systems.
  • D. Authorware
    Authorware is a now-discontinued visual authoring tool used to create interactive multimedia and e-learning applications, originally developed and popularized by Macromedia.
  • E. SPEM
    SPEM (Software & Systems Process Engineering Metamodel) is an OMG standard modeling language used to define, document, and manage software and systems development processes.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f4e7e588190b37e2413bc649198 completed April 10, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e8d27288190bdf32acd600141db completed May 2, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:53 p.m.