Triple

T18747129
Position Surface form Disambiguated ID Type / Status
Subject Zafar E458432 entity
Predicate languageUsed P238 FINISHED
Object Sabaic NE NERFINISHED

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: Sabaic | Statement: [Zafar, languageUsed, Sabaic]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sabaic
Context triple: [Zafar, languageUsed, Sabaic]
  • A. Sabaic chosen
    Sabaic is an ancient South Arabian Semitic language once used in inscriptions and documents in what is now Yemen.
  • B. Sabaot
    Sabaot is a Southern Nilotic language spoken primarily by the Sabaot people in the Mount Elgon region of Kenya and Uganda.
  • C. Sabaot language
    The Sabaot language is a Nilotic language spoken by the Sabaot people of western Kenya and eastern Uganda, closely associated with the Kalenjin language cluster.
  • D. Sakaarian
    Sakaarian is the native language spoken by the inhabitants of the planet Sakaar in the Marvel universe.
  • E. Basaa
    Basaa is a Bantu language spoken primarily by the Basaa people in Cameroon.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d394dc308190b6725073f5db324c completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e576936cf08190b3c0d2f4e8a616fc completed April 20, 2026, 12:42 a.m.
Created at: April 10, 2026, 11:51 a.m.