Triple

T13809139
Position Surface form Disambiguated ID Type / Status
Subject Bunia E331837 entity
Predicate hasEthnicGroups P12220 FINISHED
Object Hema E1055539 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: Hema | Statement: [Bunia, hasEthnicGroups, Hema]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hema
Context triple: [Bunia, hasEthnicGroups, Hema]
  • A. Hema
    Hema is a central character in Jhumpa Lahiri’s short story collection "Unaccustomed Earth," representing the experiences and inner conflicts of the Indian diaspora.
  • B. Hema
    Hema is a person known primarily through their relationship with Kaushik, with no widely recognized public profile beyond this context.
  • C. Hema chosen
    Hema are an ethnic group primarily inhabiting parts of northeastern Democratic Republic of the Congo, particularly in and around the former Orientale Province.
  • D. Nimrata
    Nimrata is a given name most prominently associated with Nimrata "Nikki" Haley, an American politician and former U.S. ambassador to the United Nations.
  • E. Neela
    Neela is a central street racer and love interest in the film "The Fast and the Furious: Tokyo Drift," known for her drifting skills in Tokyo's underground racing scene.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026eae8481908b8880635e6a9152 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b08fbc348190a199c5d92e0e46be completed May 3, 2026, 8:31 p.m.
Created at: April 9, 2026, 10:12 p.m.