Triple

T3623037
Position Surface form Disambiguated ID Type / Status
Subject Atossa E76771 entity
Predicate spouse P13 FINISHED
Object Gaumata E344002 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: Gaumata | Statement: [Atossa, spouse, Gaumata]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaumata
Context triple: [Atossa, spouse, Gaumata]
  • A. Gaumata chosen
    Gaumata was a Magian priest who seized the Persian throne by impersonating the Achaemenid king Bardiya, before being overthrown by Darius I.
  • B. Otunga
    Otunga is the surname of David Otunga, an American lawyer, actor, and former professional wrestler best known for his time in WWE.
  • C. Mata-Utu
    Mata-Utu is the main town and administrative center of the French overseas collectivity of Wallis and Futuna in the South Pacific.
  • D. Gukumatz
    Gukumatz is a feathered serpent deity of the Kʼicheʼ Maya, closely associated with creation, wind, and wisdom and identified with the Mesoamerican god Quetzalcoatl.
  • E. Tabogon
    Tabogon is a coastal municipality in the province of Cebu in the Philippines, known for its agricultural lands and scenic seaside areas.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc2bc79008190abe6900adcbda8de completed March 8, 2026, 6:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69b43320955c8190910c0f15c80f41f4 completed March 13, 2026, 3:54 p.m.
Created at: March 8, 2026, 3:23 p.m.