Triple

T2322682
Position Surface form Disambiguated ID Type / Status
Subject Tabitha King E48215 entity
Predicate child P120 FINISHED
Object Owen King E40995 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: Owen King | Statement: [Tabitha King, child, Owen King]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Owen King
Context triple: [Tabitha King, child, Owen King]
  • A. Owen King chosen
    Owen King is an American author and the son of novelist Stephen King, known for his own works of fiction and collaborations with his father.
  • B. Owen Moore
    Owen Moore was an Irish-born American silent film actor best known for his early Hollywood work and his tumultuous marriage to screen star Mary Pickford.
  • C. Christopher Blake
    Christopher Blake is a stage play written by American playwright Moss Hart, best known for its dramatic exploration of family and marital conflict.
  • D. Julian Osborn
    Julian Osborn is a key character in Nevil Shute’s post-apocalyptic novel "On the Beach," portrayed as a thoughtful and stoic Australian scientist confronting the inevitability of global nuclear fallout.
  • E. Alexander Haddow
    Alexander Haddow was a Scottish epidemiologist and virologist noted for his pioneering research on insect-borne viruses, particularly in Africa.
  • 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_69a88aa308a88190b0b86c011fda7fce completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc645bac081908c0b161d0ca99aaf completed March 7, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae896b357c8190a6cdf99d5292037e completed March 9, 2026, 8:48 a.m.
Created at: March 4, 2026, 7:49 p.m.