Triple

T11984971
Position Surface form Disambiguated ID Type / Status
Subject Toby E285253 entity
Predicate fullName P16 FINISHED
Object Tobias Ragg E518332 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: Tobias Ragg | Statement: [Toby, fullName, Tobias Ragg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tobias Ragg
Context triple: [Toby, fullName, Tobias Ragg]
  • A. Tobias Ragg chosen
    Tobias Ragg is a naive and good-hearted young apprentice whose gradual realization of the horrors around him makes him one of the most tragic figures in the musical "Sweeney Todd."
  • B. Tobias
    Tobias was a Native American man from the 17th-century Wampanoag community, known primarily through his familial connection to the Sakonnet leader Awashonks.
  • C. Tobias
    Tobias is a surname of likely Hebrew origin, borne by various notable individuals including the American character actor George Tobias.
  • D. Tobias
    Tobias is the virtuous young protagonist of the biblical Book of Tobit, known for his journey with the angel Raphael and the healing of his father’s blindness.
  • E. Tobias
    Tobias is a character from the novel "Watch Over Me," playing a significant role in the story's emotional and psychological development.
  • 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_69d6ab44a77c8190a652f4b27164e4ef completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903acbb9081908fe7f8360057785c completed April 10, 2026, 2:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69f48aa73458819097a69b371350743c completed May 1, 2026, 11:12 a.m.
Created at: April 8, 2026, 9:46 p.m.