Triple

T16499236
Position Surface form Disambiguated ID Type / Status
Subject Bed-Ins for Peace E400759 entity
Predicate hasParticipant P149 FINISHED
Object Yoko Ono E93289 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: Yoko Ono | Statement: [Bed-Ins for Peace, hasParticipant, Yoko Ono]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yoko Ono
Context triple: [Bed-Ins for Peace, hasParticipant, Yoko Ono]
  • A. Yoko Ono chosen
    Yoko Ono is a Japanese multimedia artist, musician, and peace activist known for her avant-garde work and her marriage and collaborations with John Lennon.
  • B. Yoko Satō
    Yoko Satō is a Japanese individual known for bearing the surname Satō, which is one of the most common family names in Japan.
  • C. Yoko
    Yoko is a Japanese given name commonly used for women and borne by various notable figures in arts, literature, and entertainment.
  • D. Yoko Littner
    Yoko Littner is a prominent, sharp-shooting heroine from the anime series "Tengen Toppa Gurren Lagann," known for her combat skills, distinctive appearance, and strong-willed personality.
  • E. Joan Jonas
    Joan Jonas is an influential American visual artist and pioneer of performance and video art whose experimental, multimedia works have significantly shaped contemporary art since the late 1960s.
  • 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_69d88381f6148190819958a038be990e completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e35b96881908c9d339eea9e4314 completed April 18, 2026, 7:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00758bc924819099f29d01bd8a02a0 completed May 10, 2026, 12:09 p.m.
Created at: April 10, 2026, 5:14 a.m.