Triple

T345805
Position Surface form Disambiguated ID Type / Status
Subject Ralph Nelson E6938 entity
Predicate directed P7373 FINISHED
Object Charly E44760 NE FINISHED

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: Charly | Statement: [Ralph Nelson, directed, Charly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charly
Context triple: [Ralph Nelson, directed, Charly]
  • A. Charly chosen
    Charly is a 1968 American drama film directed by Ralph Nelson, best known for Cliff Robertson’s Oscar-winning portrayal of a man with intellectual disabilities who undergoes an experimental intelligence-enhancing procedure.
  • B. Lulu
    Lulu is a common feminine given name or nickname, often used as a diminutive form of names like Louise.
  • C. Christine
    Christine is the birth name of Chrissy Teigen, an American model, television personality, and cookbook author.
  • D. Niña
    Niña was one of the three ships in Christopher Columbus’s 1492 voyage across the Atlantic, notable for its role in the first European expedition to the Americas.
  • E. Mina
    Mina is a valley and neighborhood near Mecca in Saudi Arabia that serves as a major site for key Hajj rituals, including the symbolic stoning of the devil.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a2e7951ba08190960e90823b5078f3 completed Feb. 28, 2026, 1:03 p.m.
NER Named-entity recognition batch_69a2eb0240e88190bc70784772f5fa30 completed Feb. 28, 2026, 1:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3e014e2748190b4c45b16186a0d66 completed March 1, 2026, 6:43 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.