Triple

T15716715
Position Surface form Disambiguated ID Type / Status
Subject Jeliza-Rose E380979 entity
Predicate hasFather P1908 FINISHED
Object Noah
Noah is a character in the film "Tideland," serving as the troubled, drug-addicted father of the young protagonist Jeliza-Rose.
 E1172738 NE FINISHED

How this triple was built (4 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: [Jeliza-Rose, hasFather, Noah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Noah
Context triple: [Jeliza-Rose, hasFather, 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
    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.
  • C. Noah
    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.
  • D. 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.
  • E. Noah
    Noah is a character in the 2007 horror film "The Underground," portrayed as part of the movie’s dark, suspenseful narrative.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Noah
Triple: [Jeliza-Rose, hasFather, Noah]
Generated description
Noah is a character in the film "Tideland," serving as the troubled, drug-addicted father of the young protagonist Jeliza-Rose.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Noah
Target entity description: Noah is a character in the film "Tideland," serving as the troubled, drug-addicted father of the young protagonist Jeliza-Rose.
  • 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
    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.
  • C. Noah
    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.
  • D. 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.
  • E. Noah
    Noah is a character in the 2007 horror film "The Underground," portrayed as part of the movie’s dark, suspenseful narrative.
  • F. None of above. chosen

Provenance (5 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_69d86d9bf930819082b30cf6d169297c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f91beb08190bd91bf9306737c3b completed April 16, 2026, 2:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff7583609c8190a80421fce649900f completed May 9, 2026, 5:57 p.m.
NEDg Description generation batch_69ff76deb1948190bc49825719ac97d5 completed May 9, 2026, 6:03 p.m.
NED2 Entity disambiguation (via description) batch_69ff77642ba4819095c1acc65da06135 completed May 9, 2026, 6:05 p.m.
Created at: April 10, 2026, 4:45 a.m.