Triple

T6777336
Position Surface form Disambiguated ID Type / Status
Subject Warekena language E155590 entity
Predicate hasAlternativeName P39 FINISHED
Object Arekena E618341 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: Arekena | Statement: [Warekena language, hasAlternativeName, Arekena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arekena
Context triple: [Warekena language, hasAlternativeName, Arekena]
  • A. Uarekena chosen
    Uarekena is an indigenous Arawakan language spoken by the Warekena people in parts of Brazil and Venezuela.
  • B. Itumbiara
    Itumbiara is a municipality in the Brazilian state of Goiás, known for its strategic location on the Paranaíba River and its role as a regional economic and transportation hub.
  • C. Egushawa
    Egushawa was an 18th-century Ottawa war chief known for his prominent leadership in Native American resistance against United States expansion in the Old Northwest.
  • D. Punu
    Punu is a Bantu language spoken primarily by the Punu people of southern Gabon and neighboring regions.
  • E. Rumueme
    Rumueme is a prominent urban community in Rivers State, Nigeria, forming part of the greater Port Harcourt metropolitan area.
  • 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_69c688162bf8819088b664b5c3b5be7a completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d26725208190b64935cfd08b2aff completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c71a8263508190ad5cace74d7d7ac2 completed March 28, 2026, 12:02 a.m.
Created at: March 27, 2026, 2:13 p.m.