Triple

T22696613
Position Surface form Disambiguated ID Type / Status
Subject One Day It'll All Make Sense E561192 entity
Predicate producer P490 FINISHED
Object Ynot 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: Ynot | Statement: [One Day It'll All Make Sense, producer, Ynot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ynot
Context triple: [One Day It'll All Make Sense, producer, Ynot]
  • A. Ynot chosen
    Ynot is a film production company known for its work on the acclaimed Mexican romantic drama "Like Water for Chocolate."
  • B. Notsi
    Notsi is an Oceanic language spoken in parts of Papua New Guinea, belonging to the Meso-Melanesian branch of the Austronesian language family.
  • C. Nohr
    Nohr is a dark, militaristic kingdom in the game Fire Emblem Fates, known for its harsh environment, power struggles, and central role in the story’s political conflict.
  • D. Noth
    Noth is a surname most prominently associated with American actor Chris Noth, known for his roles in television series such as "Sex and the City" and "Law & Order."
  • E. Nebelong
    Nebelong is a Danish surname most notably associated with 19th-century architect Johan Henrik Nebelong.
  • 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_69e2454e615481909c177440be559d2c completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1789f26848190bcc5a99e3ed909e7 completed April 29, 2026, 3:18 a.m.
Created at: April 17, 2026, 3:14 p.m.