Triple

T3972620
Position Surface form Disambiguated ID Type / Status
Subject Musiq Soulchild E92367 entity
Predicate notableWork P4 FINISHED
Object Teachme E249518 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: Teachme | Statement: [Musiq Soulchild, notableWork, Teachme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Teachme
Context triple: [Musiq Soulchild, notableWork, Teachme]
  • A. Khanmigo (AI education tool by Khan Academy)
    Khanmigo is Khan Academy’s AI-powered tutoring and teaching assistant designed to provide interactive, personalized support for students and educators across a wide range of subjects.
  • B. TeachText
    TeachText was a simple text-editing application bundled with early versions of the classic Mac OS, primarily used for reading documentation and creating basic text files.
  • C. Teach Me chosen
    Teach Me is a song featured on the album "All I Want Is You" by American singer-songwriter Miguel.
  • D. OpenLearning
    OpenLearning is an online education platform that hosts and delivers massive open online courses (MOOCs) from institutions and educators worldwide.
  • E. Curriki
    Curriki is an education-focused nonprofit organization that provides free, open-source digital learning resources and tools for teachers and students worldwide.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef996ff6c8190ba8cc490e4744b95 completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5400fa9ac8190adf70a4c49eac32c completed March 14, 2026, 11:01 a.m.
Created at: March 9, 2026, 3:32 p.m.