Triple

T5165924
Position Surface form Disambiguated ID Type / Status
Subject Pachamama E116554 entity
Predicate meaningOfName P1966 FINISHED
Object World Mother E77587 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: World Mother | Statement: [Pachamama, meaningOfName, World Mother]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: World Mother
Context triple: [Pachamama, meaningOfName, World Mother]
  • A. Great Mother chosen
    Great Mother is an epithet of Gaia that emphasizes her role as the primordial earth goddess and universal mother figure in Greek mythology.
  • B. Mamayi
    Mamayi was a powerful 14th-century military and political leader of the Golden Horde who played a central role in its internal power struggles and conflicts with emerging Russian principalities.
  • C. Matua
    Matua is a volcanic island in the central Kuril Islands chain, notable for its World War II-era Japanese military installations and strategic location in the northwest Pacific.
  • D. Amma
    Amma is a fictional female protagonist, likely a central figure in a narrative focused on a girl or woman’s experiences.
  • E. Marella
    Marella is an Italian feminine given name, notably borne by Marella Agnelli, a prominent socialite, art collector, and style icon.
  • 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_69bd445edb3881909b93b34d260717fc completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd792af4648190934cf2db523f6921 completed March 20, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69bed937bd8c81909569f7205044aa5a completed March 21, 2026, 5:45 p.m.
Created at: March 20, 2026, 1:44 p.m.