Triple

T19731110
Position Surface form Disambiguated ID Type / Status
Subject Matsya kingdom E473854 entity
Predicate hasRoyalFamilyMember P68121 FINISHED
Object Satanika 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: Satanika | Statement: [Matsya kingdom, hasRoyalFamilyMember, Satanika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Satanika
Context triple: [Matsya kingdom, hasRoyalFamilyMember, Satanika]
  • A. Satanika chosen
    Satanika is a character from the Indian epic Mahabharata, known as one of the sons of Nakula and a warrior prince of the Pandava lineage.
  • B. Satanaya
    Satanaya is a central matriarchal figure and wise culture-heroine in the Nart sagas of the Caucasus, often portrayed as the mother and counselor of the Nart heroes.
  • C. Shatana
    Shatana is a character from the Nart sagas, the traditional epic cycle of the North Caucasus peoples.
  • D. Satana
    Satana is a Marvel Comics supernatural antiheroine and sorceress, the half-demon daughter of Satan and sister of Daimon Hellstrom.
  • E. Satana
    Satana is a town in the Nashik district of Maharashtra, India, known for its agricultural markets and proximity to several religious and historical sites.
  • 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_69d8e517ebd48190979ee76723bcfadf completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e649fd18148190a6e85b2be0069dde completed April 20, 2026, 3:45 p.m.
Created at: April 10, 2026, 1:47 p.m.