Triple

T4126774
Position Surface form Disambiguated ID Type / Status
Subject Nama people E92744 entity
Predicate ethnonym P4709 FINISHED
Object Nama E85862 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: Nama | Statement: [Nama people, ethnonym, Nama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nama
Context triple: [Nama people, ethnonym, Nama]
  • A. Nama chosen
    Nama is a Khoe language spoken primarily by the Nama people in Namibia and neighboring regions of southern Africa.
  • B. Nome
    Nome is a remote coastal city in western Alaska known historically for its gold rush heritage and as a key transportation and supply hub on the Bering Sea.
  • C. Na
    Na is the given name of Chinese professional tennis player Li Na, a former world No. 2 and two-time Grand Slam singles champion.
  • D. NAM
    NAM is the commonly used acronym for the National Academy of Medicine, a leading U.S. nonprofit institution that provides expert advice on health, medicine, and biomedical science.
  • E. NAM
    NAM is the commonly used abbreviation for the Non-Aligned Movement, an international grouping of states that sought to remain independent from major power blocs during the Cold War and beyond.
  • 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_69aed9685f70819086932777aec8d959 completed March 9, 2026, 2:30 p.m.
NER Named-entity recognition batch_69af0219f0e48190b0a925f09d858d65 completed March 9, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576b96e588190bdf346a66a95138a completed March 14, 2026, 2:54 p.m.
Created at: March 9, 2026, 3:42 p.m.