Triple

T483512
Position Surface form Disambiguated ID Type / Status
Subject Sudanese Arabic E9822 entity
Predicate influencedBy P9 FINISHED
Object Fur language E49227 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: Fur language | Statement: [Sudanese Arabic, influencedBy, Fur language]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fur language
Context triple: [Sudanese Arabic, influencedBy, Fur language]
  • A. Fur language chosen
    The Fur language is an Eastern Sudanic language spoken primarily by the Fur people of western Sudan, especially in the Darfur region.
  • B. Fox language
    Fox language is a Native American Algonquian language traditionally spoken by the Meskwaki (Fox), Sauk, and Kickapoo peoples of the central United States.
  • C. Fang language
    Fang is a Bantu language spoken primarily by the Fang people of Equatorial Guinea, Gabon, and Cameroon, notable for its significant influence on local varieties of Spanish and French.
  • D. Tat language
    Tat language is an endangered Southwestern Iranian language spoken primarily by the Tat people of Azerbaijan and neighboring regions, distinct from but related to Judeo-Tat.
  • E. Taman languages
    Taman languages are a small group of closely related Nilo-Saharan languages spoken primarily in eastern Chad and western Sudan.
  • 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_69a2e802e2908190ab17c9479e0b6412 completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2f0b8fe6081909f8ab87bfda6b2d8 completed Feb. 28, 2026, 1:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69a4711ea1dc8190ac4bf0efaf0890b7 completed March 1, 2026, 5:02 p.m.
Created at: Feb. 28, 2026, 1:12 p.m.