Triple

T1832750
Position Surface form Disambiguated ID Type / Status
Subject Owen King E40995 entity
Predicate name P16 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: [Owen King, name, Owen King]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Owen King
Context triple: [Owen King, name, 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. Alexander Haddow
    Alexander Haddow was a Scottish epidemiologist and virologist noted for his pioneering research on insect-borne viruses, particularly in Africa.
  • E. Matthew Talbot
    Matthew Talbot was an early 19th-century American politician from Georgia who briefly served as the state's governor and was influential enough that Talbot County was named in his honor.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb024287c8190b68aa070e556a381 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb9f3354819097ce858a8706c324 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:33 p.m.