Triple

T18483088
Position Surface form Disambiguated ID Type / Status
Subject Double Up E451613 entity
Predicate hasTrack P3284 FINISHED
Object From Scratch 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: From Scratch | Statement: [Double Up, hasTrack, From Scratch]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: From Scratch
Context triple: [Double Up, hasTrack, From Scratch]
  • A. From Scratch chosen
    From Scratch is a romantic drama miniseries on Netflix that follows an American woman’s transformative love story in Italy, based on Tembi Locke’s memoir and starring Zoe Saldana.
  • B. Back to Scratch
    "Back to Scratch" is a studio album by Welsh singer Charlotte Church that marked her transition from classical crossover child star to a more mature pop and rock-oriented sound.
  • C. Learn You Inside Out
    "Learn You Inside Out" is a song by the Canadian rock band Nickelback from their 2008 album "Dark Horse."
  • D. From the Ground Up
    "From the Ground Up" is a romantic country ballad by American duo Dan + Shay that became one of their signature hits.
  • E. From the Ground Up
    From the Ground Up is a nonfiction book by historian James R. Hansen that explores the development and culture of aviation and aerospace from an insider’s perspective.
  • 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e531d49a1881908cc2ad6132953c96 completed April 19, 2026, 7:49 p.m.
Created at: April 10, 2026, 11:35 a.m.