Triple

T22368247
Position Surface form Disambiguated ID Type / Status
Subject Noah Jupe E552966 entity
Predicate givenName P17 FINISHED
Object Noah 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: Noah | Statement: [Noah Jupe, givenName, Noah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noah
Context triple: [Noah Jupe, givenName, Noah]
  • A. Noah
    Noah is a 2014 biblical epic film directed by Darren Aronofsky, in which Russell Crowe stars as the titular patriarch tasked with building an ark to survive a divinely sent flood.
  • B. Noah chosen
    Noah is a masculine given name of Hebrew origin meaning "rest" or "comfort," widely used in many cultures and popular in contemporary English-speaking countries.
  • C. Noah
    Noah is the central protagonist of the web series "Dark," whose complex journey through time and moral ambiguity drives much of the show's mystery and tension.
  • D. Noah
    Noah is a character in the 2007 horror film "The Underground," portrayed as part of the movie’s dark, suspenseful narrative.
  • E. Noah
    Noah is a character in the film "Tideland," serving as the troubled, drug-addicted father of the young protagonist Jeliza-Rose.
  • 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_69e11e4affcc8190ba7c27d29062558d completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1580229688190a6e5e02b484033f7 completed April 29, 2026, 12:59 a.m.
Created at: April 16, 2026, 8:44 p.m.