Triple

T17036741
Position Surface form Disambiguated ID Type / Status
Subject Ken Angrok E413339 entity
Predicate spouse P13 FINISHED
Object Ken Dedes E413340 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: Ken Dedes | Statement: [Ken Angrok, spouse, Ken Dedes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ken Dedes
Context triple: [Ken Angrok, spouse, Ken Dedes]
  • A. Ken Dedes chosen
    Ken Dedes is a legendary Javanese queen regarded as the first queen of the Singhasari kingdom and a central figure in Indonesian historical and mythological narratives.
  • B. Andrew Vassiliadis
    Andrew Vassiliadis is an American businessman and sports executive best known for owning and leading the USL Championship soccer club San Diego Loyal SC.
  • C. Frank Klopas
    Frank Klopas is a Greek-American former professional soccer player and coach best known for his long-standing association with the Chicago Fire as both a player and manager.
  • D. John Kapelos
    John Kapelos is a Canadian character actor best known for his roles in films like The Breakfast Club and numerous television series.
  • E. Michael Trikilis
    Michael Trikilis was an American television and film producer best known for his work on Playboy-related projects and various feature films in the late 20th century.
  • 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d8f26f50819085dfd0fbecd6394d completed April 18, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b5b71f48190b6c865d57668b5d1 completed May 10, 2026, 11:57 p.m.
Created at: April 10, 2026, 5:33 a.m.