Triple

T3285590
Position Surface form Disambiguated ID Type / Status
Subject Anung Un Rama E68973 entity
Predicate mother P120 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: [Anung Un Rama, mother, Sarah Hughes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sarah Hughes
Context triple: [Anung Un Rama, mother, 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. 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."
  • D. Michelle Kwan
    Michelle Kwan is an American figure skating icon and two-time Olympic medalist renowned for her artistry, consistency, and dominance in women’s figure skating during the late 1990s and early 2000s.
  • E. Gracie Gold
    Gracie Gold is an American figure skater known for being a U.S. national champion and competing in the 2014 Winter Olympics.
  • 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_69ad859c463481909ca4be267336c290 completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb03918c48190987d7cfd3bda9716 completed March 8, 2026, 5:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69b2e85b6a1081908581b2040b8ce261 completed March 12, 2026, 4:22 p.m.
Created at: March 8, 2026, 3:10 p.m.