Triple

T13237735
Position Surface form Disambiguated ID Type / Status
Subject Young, New South Wales E315195 entity
Predicate hasHighSchool P113 FINISHED
Object Young High School E348580 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: Young High School | Statement: [Young, New South Wales, hasHighSchool, Young High School]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Young High School
Context triple: [Young, New South Wales, hasHighSchool, Young High School]
  • A. Young High School chosen
    Young High School is an educational institution serving secondary-level students in the community of Young.
  • B. Young Adult
    Young Adult is a 2011 dark comedy-drama film directed by Jason Reitman and written by Diablo Cody, starring Charlize Theron as a troubled writer who returns to her hometown.
  • C. Young Adult
    "Young Adult" is a satirical novel by Canadian writer Russell Smith that explores the hedonistic, self-absorbed lives of young urban professionals.
  • D. Teenagers
    "Teenagers" is a punk-influenced rock song by My Chemical Romance that critiques adult fear and control of youth culture.
  • E. Junior
    Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98d56da008190af55da3a9e7ffd4d completed April 10, 2026, 11:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6ff323a3c8190b46b24e69e653105 completed May 3, 2026, 7:54 a.m.
Created at: April 9, 2026, 9:22 p.m.