Triple

T18779996
Position Surface form Disambiguated ID Type / Status
Subject Aulë E459231 entity
Predicate alsoKnownAs P39 FINISHED
Object The Maker 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: The Maker | Statement: [Aulë, alsoKnownAs, The Maker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Maker
Context triple: [Aulë, alsoKnownAs, The Maker]
  • A. The Maker chosen
    "The Maker" is a track by the electronic music producer Teatro, likely showcasing his signature atmospheric and melodic style.
  • B. Makers
    Makers is a science fiction novel by Cory Doctorow that explores a near-future maker culture, disruptive innovation, and the social and economic upheavals caused by rapid technological change.
  • C. The Mind of the Maker
    The Mind of the Maker is a theological and philosophical work by Dorothy L. Sayers that explores the nature of human creativity as an analogy to the Christian doctrine of the Trinity.
  • D. El hacedor
    El hacedor is a 1960 collection of short prose pieces and poems by Jorge Luis Borges that explores themes of time, identity, and the nature of authorship in his characteristically metafictional style.
  • E. Amaker
    Amaker is the surname of Tommy Amaker, an American college basketball coach and former player best known for coaching at Harvard University.
  • 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_69d8d396f54c8190ba49db31e8743842 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5933e35a481908c21f7f488e1dd99 completed April 20, 2026, 2:45 a.m.
Created at: April 10, 2026, 11:52 a.m.