Triple

T18762730
Position Surface form Disambiguated ID Type / Status
Subject Jeffrey Levy-Hinte E458812 entity
Predicate notableWork P4 FINISHED
Object Thirteen NE NERFINISHED

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: Thirteen | Statement: [Jeffrey Levy-Hinte, notableWork, Thirteen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Thirteen
Context triple: [Jeffrey Levy-Hinte, notableWork, Thirteen]
  • A. Thirteen
    Thirteen is a studio album by American country and folk singer-songwriter Emmylou Harris.
  • B. Thirteen chosen
    Thirteen is a 2003 coming-of-age drama film co-written by and starring Nikki Reed that explores the turbulent adolescence of a thirteen-year-old girl.
  • C. Thirteen
    Thirteen is a steel roller coaster at Alton Towers Resort in the UK, known for its surprise vertical drop section and psychological horror theme.
  • D. Thirteen
    Thirteen is the nickname of Dr. Remy Hadley, a physician character from the television series "House."
  • E. Thirteen
    Thirteen is a powerful merchant council in the city of Qarth in the "A Song of Ice and Fire" series and its TV adaptation "Game of Thrones."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d395dba0819087568404508590cb completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e58d80a954819083946dafc0c7af05 completed April 20, 2026, 2:20 a.m.
Created at: April 10, 2026, 11:52 a.m.