Triple

T14626016
Position Surface form Disambiguated ID Type / Status
Subject Genevieve Hughes E343347 entity
Predicate notableRelative P367 FINISHED
Object Sarah Hughes E44108 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: Sarah Hughes | Statement: [Genevieve Hughes, notableRelative, Sarah Hughes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarah Hughes
Context triple: [Genevieve Hughes, notableRelative, Sarah Hughes]
  • A. Sarah Hughes chosen
    Sarah Hughes is an American figure skater best known for winning the ladies' singles gold medal at the 2002 Winter Olympics.
  • B. Tara Lipinski
    Tara Lipinski is an American figure skater who became the youngest Olympic ladies' singles champion in history when she won gold at the 1998 Winter Games.
  • C. Kristi Yamaguchi
    Kristi Yamaguchi is an American figure skater and 1992 Olympic gold medalist renowned for her artistry and technical skill on the ice.
  • D. Stacy Hamilton
    Stacy Hamilton is a teenage girl navigating relationships, sexuality, and growing up in the 1982 coming-of-age film "Fast Times at Ridgemont High."
  • E. Jamie Linden
    Jamie Linden is an American screenwriter and film director known for writing movies such as "We Are Marshall," "Dear John," and the financial thriller "Money Monster."
  • 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_69d822dffc3c8190aa173b90761bffda completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb46a4a9081908472b0a542028a7f completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdd5d0514081908c2bdc4fb77b1a7a completed May 8, 2026, 12:23 p.m.
Created at: April 10, 2026, 1:26 a.m.