Triple

T20056477
Position Surface form Disambiguated ID Type / Status
Subject Noah Grant E499349 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 Grant, givenName, Noah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noah
Context triple: [Noah Grant, givenName, Noah]
  • A. Noah
    Noah is a character in the film "Tideland," serving as the troubled, drug-addicted father of the young protagonist Jeliza-Rose.
  • B. 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.
  • C. Noah
    Noah is a central prophet in the Abrahamic traditions, best known for building an ark to survive a divinely sent flood meant to cleanse the world.
  • D. 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.
  • E. 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.
  • 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e663337d0c8190b82422802396cd67 completed April 20, 2026, 5:32 p.m.
Created at: April 11, 2026, 3:38 p.m.