Triple

T5714183
Position Surface form Disambiguated ID Type / Status
Subject North Hollywood High School E125981 entity
Predicate hasNotableAlumnus P51 FINISHED
Object Tom Selleck E529996 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: Tom Selleck | Statement: [North Hollywood High School, hasNotableAlumnus, Tom Selleck]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Selleck
Context triple: [North Hollywood High School, hasNotableAlumnus, Tom Selleck]
  • A. Tom Selleck chosen
    Tom Selleck is an American actor best known for his starring role as private investigator Thomas Magnum in the television series "Magnum, P.I."
  • B. Robert Davi
    Robert Davi is an American actor, singer, and director best known for his tough-guy roles in films such as "Die Hard" and the James Bond movie "Licence to Kill."
  • C. Richard Gere
    Richard Gere is an American actor known for his leading roles in films such as "American Gigolo," "An Officer and a Gentleman," and "Pretty Woman."
  • D. James Woods
    James Woods is an American actor known for his intense performances in film and television, including acclaimed roles in movies such as "Salvador," "Videodrome," and "Casino."
  • E. James Garner
    James Garner was an American actor best known for his charming, laid-back roles in television series like "Maverick" and "The Rockford Files" as well as numerous films.
  • 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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024b6c7c8819095a92f2ccede1197 completed March 22, 2026, 5:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a77d6b081908db6e64c5a361282 completed March 22, 2026, 9:09 p.m.
Created at: March 22, 2026, 3:46 p.m.