Triple

T21454964
Position Surface form Disambiguated ID Type / Status
Subject Kris Parker E529316 entity
Predicate notableWork P4 FINISHED
Object Edutainment NE NERFINISHED

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: Edutainment | Statement: [Kris Parker, notableWork, Edutainment]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Edutainment
Context triple: [Kris Parker, notableWork, Edutainment]
  • A. Edutainment chosen
    Edutainment is a socially conscious hip-hop album by KRS-One’s group Boogie Down Productions that blends education and entertainment to address political and social issues.
  • B. Edu
    Edu is a common shortened form of the given name Eduardo, often used as an informal nickname.
  • C. Edu
    Edu is a local government area in Kwara State, Nigeria, known for its predominantly Nupe-speaking communities and agrarian economy.
  • D. EDU
    EDU is the commonly used abbreviation for the European Defence Union, a proposed framework for deeper military and security cooperation among European Union member states.
  • E. EDU
    EDU is the stock ticker symbol for New Oriental Education & Technology Group, a major Chinese provider of private educational services and test preparation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c457579481909db68053ed99750c completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9e9d612e081909d00ca59a3621cc9 completed April 23, 2026, 9:43 a.m.
Created at: April 16, 2026, 6:08 p.m.