Triple

T5845682
Position Surface form Disambiguated ID Type / Status
Subject Huelén E129703 entity
Predicate hasNameLanguage P15 FINISHED
Object Mapudungun E234600 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: Mapudungun | Statement: [Huelén, hasNameLanguage, Mapudungun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mapudungun
Context triple: [Huelén, hasNameLanguage, Mapudungun]
  • A. Mapudungun chosen
    Mapudungun is an indigenous language of South America spoken primarily by the Mapuche people in Chile and Argentina.
  • B. Mazabuka
    Mazabuka is a town in southern Zambia known for its sugar industry and agricultural production.
  • C. Mwotlap
    Mwotlap is an Oceanic Austronesian language spoken on Mota Lava and nearby islands in northern Vanuatu.
  • D. Umtata
    Umtata is the former name of Mthatha, a town in South Africa’s Eastern Cape that serves as a regional economic and administrative center.
  • E. Mpondo
    The Mpondo are a Southern African ethnic group closely related to the Xhosa, known for their distinct language variety, cultural traditions, and historical kingdom in what is now South Africa’s Eastern Cape.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034dcafe88190a438034a539ffa52 completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0a1a9ffa881908b38eeddb411c4ab completed March 23, 2026, 2:12 a.m.
Created at: March 22, 2026, 3:55 p.m.