Triple

T9546092
Position Surface form Disambiguated ID Type / Status
Subject Mike Henry E230289 entity
Predicate spouse P13 FINISHED
Object Sara Henry E230289 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: Sara Henry | Statement: [Mike Henry, spouse, Sara Henry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sara Henry
Context triple: [Mike Henry, spouse, Sara Henry]
  • A. Sara Henry chosen
    Sara Henry is known as the wife of American voice actor and comedian Mike Henry, recognized for his work on shows like Family Guy.
  • B. Sara Richardson
    Sara Richardson is a television producer best known for serving as an executive producer on the crime drama series NCIS: Sydney.
  • C. Sara Allgood
    Sara Allgood was an Irish stage and film actress known for her character roles in early 20th-century theatre and classic Hollywood cinema.
  • D. Sara Williams
    Sara Williams is a sibling of American actress Michelle Williams, known primarily for her family connection to the Oscar-nominated performer.
  • E. Sara Haden
    Sara Haden was an American character actress best known for her supporting roles in classic Hollywood films of the 1930s and 1940s, including several entries in the Andy Hardy series.
  • 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_69ca847c70b8819088a0a0bad64a50d6 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9902fca081909125660ae6336d3f completed April 1, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcaaeaa08190b90ca5600deb84a2 completed April 5, 2026, 1:36 a.m.
Created at: March 30, 2026, 8:02 p.m.