Triple

T7237482
Position Surface form Disambiguated ID Type / Status
Subject Upper Guinea Creoles E155265 entity
Predicate influencedBy P9 FINISHED
Object Wolof E28117 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: Wolof | Statement: [Upper Guinea Creoles, influencedBy, Wolof]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wolof
Context triple: [Upper Guinea Creoles, influencedBy, Wolof]
  • A. Wolof chosen
    Wolof is a major Niger-Congo language spoken primarily in Senegal, The Gambia, and Mauritania, serving as a key lingua franca in the region.
  • B. Casamance Creole
    Casamance Creole is a Portuguese-based creole language spoken primarily in the Casamance region of Senegal, influenced by local West African languages.
  • C. Dioula
    Dioula is a Mande language of West Africa, widely used as a trade and lingua franca language in countries like Burkina Faso, Côte d’Ivoire, and Mali.
  • D. Tamasheq
    Tamasheq is a Berber language spoken by the Tuareg people of the central Sahara region.
  • E. Koyraboro Senni language
    The Koyraboro Senni language is a Songhay language spoken primarily along the Niger River in Mali, notably around the city of Gao.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea355e888190a97de097158933ca completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa6ad54081908a0be2d1f7d6505e completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 2:55 p.m.