Triple

T10240680
Position Surface form Disambiguated ID Type / Status
Subject John Curtis Estes E243580 entity
Predicate legalName P66 FINISHED
Object John Curtis Holmes E34928 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: John Curtis Holmes | Statement: [John Curtis Estes, legalName, John Curtis Holmes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: John Curtis Holmes
Context triple: [John Curtis Estes, legalName, John Curtis Holmes]
  • A. John Wesley Everman
    John Wesley Everman was a notable figure after whom the city of Everman, Texas, was named, likely recognized for his local influence or contributions to the area’s development.
  • B. John R. Ramsey
    John R. Ramsey was an American politician who served as a U.S. Representative from New Jersey in the early 20th century.
  • C. John Holmes chosen
    John Holmes was a famous American adult film actor of the 1970s and early 1980s, widely known for his prolific career and distinctive physical attributes.
  • D. John Holmes
    John Holmes was an American poet and influential creative writing teacher known for mentoring notable poets, including Anne Sexton, at Tufts University.
  • E. William Holmes
    William Holmes was a film editor best known for his Academy Award-winning work on the 1941 biographical war film "Sergeant York."
  • 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_69d381b0f97c819085c9b45799a5fb7c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d21e27f08190b956d351a75c7c52 completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d74fe436d48190b889ccf5884d1bb7 completed April 9, 2026, 7:06 a.m.
Created at: April 6, 2026, 11:24 a.m.