Triple

T932921
Position Surface form Disambiguated ID Type / Status
Subject Devi E20132 entity
Predicate worshippedAs P8132 FINISHED
Object Universal 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: Universal Mother | Statement: [Devi, worshippedAs, Universal Mother]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Universal Mother
Context triple: [Devi, worshippedAs, Universal 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. Virgin Unite
    Virgin Unite is the entrepreneurial foundation of the Virgin Group, created by Richard Branson to support innovative solutions to social and environmental challenges worldwide.
  • C. Abemama
    Abemama is a central Pacific atoll in the island nation of Kiribati, known for its lagoon, traditional villages, and role in the country’s colonial and wartime history.
  • D. Bachelor Mother
    Bachelor Mother is a 1939 romantic comedy film starring Ginger Rogers as a salesgirl who is mistakenly believed to be the mother of an abandoned baby.
  • E. Mam
    Mam is a Mayan language spoken primarily by the Mam people in the western highlands of Guatemala and parts of southern Mexico.
  • 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_69a493af3dc48190adb7263e6e445ea1 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b34c457c819085cbfa0c798cb4c6 completed March 1, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7ee12da388190a26f0f7944d6f5f8 completed March 4, 2026, 8:32 a.m.
Created at: March 1, 2026, 7:40 p.m.