Triple

T3239859
Position Surface form Disambiguated ID Type / Status
Subject Prince Akeem Joffer E67940 entity
Predicate friend P8712 FINISHED
Object Semmi E341024 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: Semmi | Statement: [Prince Akeem Joffer, friend, Semmi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Semmi
Context triple: [Prince Akeem Joffer, friend, Semmi]
  • A. Semmi chosen
    Semmi is a comedic supporting character in the film "Coming to America," serving as Prince Akeem's pampered and often reluctant companion from Zamunda.
  • B. Emme
    Emme is a river in Switzerland that flows through the canton of Bern and is a tributary of the Aare.
  • C. Jotijota
    Jotijota is an alternative name for the Yorta Yorta, an Aboriginal Australian people traditionally from the Murray–Goulburn region of northern Victoria and southern New South Wales.
  • D. Nellallitea
    Nellallitea is the birth name of Nella Larsen, the influential Harlem Renaissance novelist and short story writer known for exploring race and identity.
  • E. Semnoz
    Semnoz is a mountain in the French Alps known for its panoramic views over Lake Annecy and its popular hiking, skiing, and cycling routes.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaef4c0bc819095e4f84296fe7cb6 completed March 8, 2026, 5:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28eadeff481909bd48cdf51044f86 completed March 12, 2026, 10 a.m.
Created at: March 8, 2026, 3:08 p.m.